Project FOMC28914_2 services include NGS sequencing of the V1V3 region of the 16S rRNA gene amplicons from the samples. First and foremost, please
download this report, as well as the sequence raw data from the download links provided below.
These links will expire after 60 days. We cannot guarantee the availability of your data after 60 days.
Full Bioinformatics analysis service was requested. We provide many analyses, starting from the raw sequence quality and noise filtering, pair reads merging, as well as chimera filtering for the sequences, using the
DADA2 denosing algorithm and pipeline.
We also provide many downstream analyses such as taxonomy assignment, alpha and beta diversity analyses, and differential abundance analysis.
For taxonomy assignment, most informative would be the taxonomy barplots. We provide an interactive barplots to show the relative abundance of microbes at different taxonomy levels (from Phylum to species) that you can choose.
If you specify which groups of samples you want to compare for differential abundance, we provide both ANCOM and LEfSe differential abundance analysis.
The samples were processed and analyzed with the ZymoBIOMICS® Service: Targeted
Metagenomic Sequencing (Zymo Research, Irvine, CA).
DNA Extraction: If DNA extraction was performed, the following DNA
extraction kit was used according to the manufacturer’s instructions:
☑
ZymoBIOMICS®-96 MagBead DNA Kit (Zymo Research, Irvine, CA)
☐
N/A (DNA Extraction Not Performed)
Elution Volume: 50µL
Additional Notes: NA
Targeted Library Preparation: The DNA samples were prepared for targeted
sequencing with the Quick-16S™ NGS Library Prep Kit (Zymo Research, Irvine, CA).
These primers were custom designed by Zymo Research to provide the best coverage
of the 16S gene while maintaining high sensitivity. The primer sets used in this project
are marked below:
☐
Quick-16S™ Primer Set V1-V2 (Zymo Research, Irvine, CA)
☑
Quick-16S™ Primer Set V1-V3 (Zymo Research, Irvine, CA)
☐
Quick-16S™ Primer Set V3-V4 (Zymo Research, Irvine, CA)
☐
Quick-16S™ Primer Set V4 (Zymo Research, Irvine, CA)
☐
Quick-16S™ Primer Set V6-V8 (Zymo Research, Irvine, CA)
Additional Notes: NA
The sequencing library was prepared using an innovative library preparation process in
which PCR reactions were performed in real-time PCR machines to control cycles and
therefore limit PCR chimera formation. The final PCR products were quantified with
qPCR fluorescence readings and pooled together based on equal molarity. The final
pooled library was cleaned up with the Select-a-Size DNA Clean & Concentrator™
(Zymo Research, Irvine, CA), then quantified with TapeStation® (Agilent Technologies,
Santa Clara, CA) and Qubit® (Thermo Fisher Scientific, Waltham, WA).
Control Samples: The ZymoBIOMICS® Microbial Community Standard (Zymo
Research, Irvine, CA) was used as a positive control for each DNA extraction, if
performed. The ZymoBIOMICS® Microbial Community DNA Standard (Zymo Research,
Irvine, CA) was used as a positive control for each targeted library preparation.
Negative controls (i.e. blank extraction control, blank library preparation control) were
included to assess the level of bioburden carried by the wet-lab process.
Sequencing: The final library was sequenced on Illumina® NextSeq 2000™ with a p1
(Illumina, Sand Diego, CA) reagent kit (600 cycles). The sequencing was performed
with 25% PhiX spike-in.
Absolute Abundance Quantification*: A quantitative real-time PCR was set up with a
standard curve. The standard curve was made with plasmid DNA containing one copy
of the 16S gene and one copy of the fungal ITS2 region prepared in 10-fold serial
dilutions. The primers used were the same as those used in Targeted Library
Preparation. The equation generated by the plasmid DNA standard curve was used to
calculate the number of gene copies in the reaction for each sample. The PCR input
volume (2 µl) was used to calculate the number of gene copies per microliter in each
DNA sample.
The number of genome copies per microliter DNA sample was calculated by dividing
the gene copy number by an assumed number of gene copies per genome. The value
used for 16S copies per genome is 4. The value used for ITS copies per genome is 200.
The amount of DNA per microliter DNA sample was calculated using an assumed
genome size of 4.64 x 106 bp, the genome size of Escherichia coli, for 16S samples, or
an assumed genome size of 1.20 x 107 bp, the genome size of Saccharomyces
cerevisiae, for ITS samples. This calculation is shown below:
Calculated Total DNA = Calculated Total Genome Copies × Assumed Genome Size (4.64 × 106 bp) ×
Average Molecular Weight of a DNA bp (660 g/mole/bp) ÷ Avogadro’s Number (6.022 x 1023/mole)
* Absolute Abundance Quantification is only available for 16S and ITS analyses.
The absolute abundance standard curve data can be viewed in Excel here:
The absolute abundance standard curve is shown below:
The complete report of your project, including all links in this report, can be downloaded by clicking the link provided below. The downloaded file is a compressed ZIP file and once unzipped, open the file “REPORT.html” (may only shown as "REPORT" in your computer) by double clicking it. Your default web browser will open it and you will see the exact content of this report.
Please download and save the file to your computer storage device. The download link will expire after 60 days upon your receiving of this report.
Complete report download link:
To view the report, please follow the following steps:
1.
Download the .zip file from the report link above.
2.
Extract all the contents of the downloaded .zip file to your desktop.
3.
Open the extracted folder and find the "REPORT.html" (may shown as only "REPORT").
4.
Open (double-clicking) the REPORT.html file. Your default browser will open the top age of the complete report. Within the
report, there are links to view all the analyses performed for the project.
The raw NGS sequence data is available for download with the link provided below. The data is a compressed ZIP file and can be unzipped to individual sequence files.
Since this is a Pac-Bio full-length (V1V9) 16S rRNA amplicon sequencing, raw sequences are available for download in a single compressed zip file in the download link below.
After unzipping, you will find individual sequence files for each of your samples with the file extension “*.fastq.gz”.
The files are in FASTQ format and are compressed. FASTQ format is a text-based data format for storing both a biological sequence
and its corresponding quality scores. Most sequence analysis software will be able to open them.
The Sample IDs associated with the fastq files are listed in the table below:
Sample ID
Original Sample ID
Read 1 File Name
Read 2 File Name
F28914.S100
original sample ID here
zr28914_100V1V3_R1.fastq.gz
zr28914_100V1V3_R2.fastq.gz
F28914.S101
original sample ID here
zr28914_101V1V3_R1.fastq.gz
zr28914_101V1V3_R2.fastq.gz
F28914.S102
original sample ID here
zr28914_102V1V3_R1.fastq.gz
zr28914_102V1V3_R2.fastq.gz
F28914.S103
original sample ID here
zr28914_103V1V3_R1.fastq.gz
zr28914_103V1V3_R2.fastq.gz
F28914.S104
original sample ID here
zr28914_104V1V3_R1.fastq.gz
zr28914_104V1V3_R2.fastq.gz
F28914.S105
original sample ID here
zr28914_105V1V3_R1.fastq.gz
zr28914_105V1V3_R2.fastq.gz
F28914.S106
original sample ID here
zr28914_106V1V3_R1.fastq.gz
zr28914_106V1V3_R2.fastq.gz
F28914.S107
original sample ID here
zr28914_107V1V3_R1.fastq.gz
zr28914_107V1V3_R2.fastq.gz
F28914.S108
original sample ID here
zr28914_108V1V3_R1.fastq.gz
zr28914_108V1V3_R2.fastq.gz
F28914.S109
original sample ID here
zr28914_109V1V3_R1.fastq.gz
zr28914_109V1V3_R2.fastq.gz
F28914.S010
original sample ID here
zr28914_10V1V3_R1.fastq.gz
zr28914_10V1V3_R2.fastq.gz
F28914.S110
original sample ID here
zr28914_110V1V3_R1.fastq.gz
zr28914_110V1V3_R2.fastq.gz
F28914.S111
original sample ID here
zr28914_111V1V3_R1.fastq.gz
zr28914_111V1V3_R2.fastq.gz
F28914.S112
original sample ID here
zr28914_112V1V3_R1.fastq.gz
zr28914_112V1V3_R2.fastq.gz
F28914.S113
original sample ID here
zr28914_113V1V3_R1.fastq.gz
zr28914_113V1V3_R2.fastq.gz
F28914.S114
original sample ID here
zr28914_114V1V3_R1.fastq.gz
zr28914_114V1V3_R2.fastq.gz
F28914.S115
original sample ID here
zr28914_115V1V3_R1.fastq.gz
zr28914_115V1V3_R2.fastq.gz
F28914.S116
original sample ID here
zr28914_116V1V3_R1.fastq.gz
zr28914_116V1V3_R2.fastq.gz
F28914.S117
original sample ID here
zr28914_117V1V3_R1.fastq.gz
zr28914_117V1V3_R2.fastq.gz
F28914.S118
original sample ID here
zr28914_118V1V3_R1.fastq.gz
zr28914_118V1V3_R2.fastq.gz
F28914.S119
original sample ID here
zr28914_119V1V3_R1.fastq.gz
zr28914_119V1V3_R2.fastq.gz
F28914.S011
original sample ID here
zr28914_11V1V3_R1.fastq.gz
zr28914_11V1V3_R2.fastq.gz
F28914.S120
original sample ID here
zr28914_120V1V3_R1.fastq.gz
zr28914_120V1V3_R2.fastq.gz
F28914.S121
original sample ID here
zr28914_121V1V3_R1.fastq.gz
zr28914_121V1V3_R2.fastq.gz
F28914.S122
original sample ID here
zr28914_122V1V3_R1.fastq.gz
zr28914_122V1V3_R2.fastq.gz
F28914.S123
original sample ID here
zr28914_123V1V3_R1.fastq.gz
zr28914_123V1V3_R2.fastq.gz
F28914.S124
original sample ID here
zr28914_124V1V3_R1.fastq.gz
zr28914_124V1V3_R2.fastq.gz
F28914.S125
original sample ID here
zr28914_125V1V3_R1.fastq.gz
zr28914_125V1V3_R2.fastq.gz
F28914.S126
original sample ID here
zr28914_126V1V3_R1.fastq.gz
zr28914_126V1V3_R2.fastq.gz
F28914.S127
original sample ID here
zr28914_127V1V3_R1.fastq.gz
zr28914_127V1V3_R2.fastq.gz
F28914.S128
original sample ID here
zr28914_128V1V3_R1.fastq.gz
zr28914_128V1V3_R2.fastq.gz
F28914.S129
original sample ID here
zr28914_129V1V3_R1.fastq.gz
zr28914_129V1V3_R2.fastq.gz
F28914.S012
original sample ID here
zr28914_12V1V3_R1.fastq.gz
zr28914_12V1V3_R2.fastq.gz
F28914.S130
original sample ID here
zr28914_130V1V3_R1.fastq.gz
zr28914_130V1V3_R2.fastq.gz
F28914.S131
original sample ID here
zr28914_131V1V3_R1.fastq.gz
zr28914_131V1V3_R2.fastq.gz
F28914.S132
original sample ID here
zr28914_132V1V3_R1.fastq.gz
zr28914_132V1V3_R2.fastq.gz
F28914.S133
original sample ID here
zr28914_133V1V3_R1.fastq.gz
zr28914_133V1V3_R2.fastq.gz
F28914.S134
original sample ID here
zr28914_134V1V3_R1.fastq.gz
zr28914_134V1V3_R2.fastq.gz
F28914.S135
original sample ID here
zr28914_135V1V3_R1.fastq.gz
zr28914_135V1V3_R2.fastq.gz
F28914.S136
original sample ID here
zr28914_136V1V3_R1.fastq.gz
zr28914_136V1V3_R2.fastq.gz
F28914.S137
original sample ID here
zr28914_137V1V3_R1.fastq.gz
zr28914_137V1V3_R2.fastq.gz
F28914.S138
original sample ID here
zr28914_138V1V3_R1.fastq.gz
zr28914_138V1V3_R2.fastq.gz
F28914.S139
original sample ID here
zr28914_139V1V3_R1.fastq.gz
zr28914_139V1V3_R2.fastq.gz
F28914.S013
original sample ID here
zr28914_13V1V3_R1.fastq.gz
zr28914_13V1V3_R2.fastq.gz
F28914.S140
original sample ID here
zr28914_140V1V3_R1.fastq.gz
zr28914_140V1V3_R2.fastq.gz
F28914.S141
original sample ID here
zr28914_141V1V3_R1.fastq.gz
zr28914_141V1V3_R2.fastq.gz
F28914.S142
original sample ID here
zr28914_142V1V3_R1.fastq.gz
zr28914_142V1V3_R2.fastq.gz
F28914.S143
original sample ID here
zr28914_143V1V3_R1.fastq.gz
zr28914_143V1V3_R2.fastq.gz
F28914.S144
original sample ID here
zr28914_144V1V3_R1.fastq.gz
zr28914_144V1V3_R2.fastq.gz
F28914.S145
original sample ID here
zr28914_145V1V3_R1.fastq.gz
zr28914_145V1V3_R2.fastq.gz
F28914.S146
original sample ID here
zr28914_146V1V3_R1.fastq.gz
zr28914_146V1V3_R2.fastq.gz
F28914.S147
original sample ID here
zr28914_147V1V3_R1.fastq.gz
zr28914_147V1V3_R2.fastq.gz
F28914.S148
original sample ID here
zr28914_148V1V3_R1.fastq.gz
zr28914_148V1V3_R2.fastq.gz
F28914.S149
original sample ID here
zr28914_149V1V3_R1.fastq.gz
zr28914_149V1V3_R2.fastq.gz
F28914.S014
original sample ID here
zr28914_14V1V3_R1.fastq.gz
zr28914_14V1V3_R2.fastq.gz
F28914.S150
original sample ID here
zr28914_150V1V3_R1.fastq.gz
zr28914_150V1V3_R2.fastq.gz
F28914.S151
original sample ID here
zr28914_151V1V3_R1.fastq.gz
zr28914_151V1V3_R2.fastq.gz
F28914.S152
original sample ID here
zr28914_152V1V3_R1.fastq.gz
zr28914_152V1V3_R2.fastq.gz
F28914.S153
original sample ID here
zr28914_153V1V3_R1.fastq.gz
zr28914_153V1V3_R2.fastq.gz
F28914.S154
original sample ID here
zr28914_154V1V3_R1.fastq.gz
zr28914_154V1V3_R2.fastq.gz
F28914.S155
original sample ID here
zr28914_155V1V3_R1.fastq.gz
zr28914_155V1V3_R2.fastq.gz
F28914.S156
original sample ID here
zr28914_156V1V3_R1.fastq.gz
zr28914_156V1V3_R2.fastq.gz
F28914.S157
original sample ID here
zr28914_157V1V3_R1.fastq.gz
zr28914_157V1V3_R2.fastq.gz
F28914.S158
original sample ID here
zr28914_158V1V3_R1.fastq.gz
zr28914_158V1V3_R2.fastq.gz
F28914.S159
original sample ID here
zr28914_159V1V3_R1.fastq.gz
zr28914_159V1V3_R2.fastq.gz
F28914.S015
original sample ID here
zr28914_15V1V3_R1.fastq.gz
zr28914_15V1V3_R2.fastq.gz
F28914.S160
original sample ID here
zr28914_160V1V3_R1.fastq.gz
zr28914_160V1V3_R2.fastq.gz
F28914.S161
original sample ID here
zr28914_161V1V3_R1.fastq.gz
zr28914_161V1V3_R2.fastq.gz
F28914.S162
original sample ID here
zr28914_162V1V3_R1.fastq.gz
zr28914_162V1V3_R2.fastq.gz
F28914.S163
original sample ID here
zr28914_163V1V3_R1.fastq.gz
zr28914_163V1V3_R2.fastq.gz
F28914.S164
original sample ID here
zr28914_164V1V3_R1.fastq.gz
zr28914_164V1V3_R2.fastq.gz
F28914.S165
original sample ID here
zr28914_165V1V3_R1.fastq.gz
zr28914_165V1V3_R2.fastq.gz
F28914.S166
original sample ID here
zr28914_166V1V3_R1.fastq.gz
zr28914_166V1V3_R2.fastq.gz
F28914.S167
original sample ID here
zr28914_167V1V3_R1.fastq.gz
zr28914_167V1V3_R2.fastq.gz
F28914.S168
original sample ID here
zr28914_168V1V3_R1.fastq.gz
zr28914_168V1V3_R2.fastq.gz
F28914.S169
original sample ID here
zr28914_169V1V3_R1.fastq.gz
zr28914_169V1V3_R2.fastq.gz
F28914.S016
original sample ID here
zr28914_16V1V3_R1.fastq.gz
zr28914_16V1V3_R2.fastq.gz
F28914.S170
original sample ID here
zr28914_170V1V3_R1.fastq.gz
zr28914_170V1V3_R2.fastq.gz
F28914.S171
original sample ID here
zr28914_171V1V3_R1.fastq.gz
zr28914_171V1V3_R2.fastq.gz
F28914.S172
original sample ID here
zr28914_172V1V3_R1.fastq.gz
zr28914_172V1V3_R2.fastq.gz
F28914.S173
original sample ID here
zr28914_173V1V3_R1.fastq.gz
zr28914_173V1V3_R2.fastq.gz
F28914.S174
original sample ID here
zr28914_174V1V3_R1.fastq.gz
zr28914_174V1V3_R2.fastq.gz
F28914.S175
original sample ID here
zr28914_175V1V3_R1.fastq.gz
zr28914_175V1V3_R2.fastq.gz
F28914.S176
original sample ID here
zr28914_176V1V3_R1.fastq.gz
zr28914_176V1V3_R2.fastq.gz
F28914.S177
original sample ID here
zr28914_177V1V3_R1.fastq.gz
zr28914_177V1V3_R2.fastq.gz
F28914.S178
original sample ID here
zr28914_178V1V3_R1.fastq.gz
zr28914_178V1V3_R2.fastq.gz
F28914.S179
original sample ID here
zr28914_179V1V3_R1.fastq.gz
zr28914_179V1V3_R2.fastq.gz
F28914.S017
original sample ID here
zr28914_17V1V3_R1.fastq.gz
zr28914_17V1V3_R2.fastq.gz
F28914.S180
original sample ID here
zr28914_180V1V3_R1.fastq.gz
zr28914_180V1V3_R2.fastq.gz
F28914.S181
original sample ID here
zr28914_181V1V3_R1.fastq.gz
zr28914_181V1V3_R2.fastq.gz
F28914.S182
original sample ID here
zr28914_182V1V3_R1.fastq.gz
zr28914_182V1V3_R2.fastq.gz
F28914.S183
original sample ID here
zr28914_183V1V3_R1.fastq.gz
zr28914_183V1V3_R2.fastq.gz
F28914.S184
original sample ID here
zr28914_184V1V3_R1.fastq.gz
zr28914_184V1V3_R2.fastq.gz
F28914.S185
original sample ID here
zr28914_185V1V3_R1.fastq.gz
zr28914_185V1V3_R2.fastq.gz
F28914.S186
original sample ID here
zr28914_186V1V3_R1.fastq.gz
zr28914_186V1V3_R2.fastq.gz
F28914.S187
original sample ID here
zr28914_187V1V3_R1.fastq.gz
zr28914_187V1V3_R2.fastq.gz
F28914.S188
original sample ID here
zr28914_188V1V3_R1.fastq.gz
zr28914_188V1V3_R2.fastq.gz
F28914.S189
original sample ID here
zr28914_189V1V3_R1.fastq.gz
zr28914_189V1V3_R2.fastq.gz
F28914.S018
original sample ID here
zr28914_18V1V3_R1.fastq.gz
zr28914_18V1V3_R2.fastq.gz
F28914.S190
original sample ID here
zr28914_190V1V3_R1.fastq.gz
zr28914_190V1V3_R2.fastq.gz
F28914.S191
original sample ID here
zr28914_191V1V3_R1.fastq.gz
zr28914_191V1V3_R2.fastq.gz
F28914.S192
original sample ID here
zr28914_192V1V3_R1.fastq.gz
zr28914_192V1V3_R2.fastq.gz
F28914.S193
original sample ID here
zr28914_193V1V3_R1.fastq.gz
zr28914_193V1V3_R2.fastq.gz
F28914.S194
original sample ID here
zr28914_194V1V3_R1.fastq.gz
zr28914_194V1V3_R2.fastq.gz
F28914.S195
original sample ID here
zr28914_195V1V3_R1.fastq.gz
zr28914_195V1V3_R2.fastq.gz
F28914.S196
original sample ID here
zr28914_196V1V3_R1.fastq.gz
zr28914_196V1V3_R2.fastq.gz
F28914.S197
original sample ID here
zr28914_197V1V3_R1.fastq.gz
zr28914_197V1V3_R2.fastq.gz
F28914.S198
original sample ID here
zr28914_198V1V3_R1.fastq.gz
zr28914_198V1V3_R2.fastq.gz
F28914.S199
original sample ID here
zr28914_199V1V3_R1.fastq.gz
zr28914_199V1V3_R2.fastq.gz
F28914.S019
original sample ID here
zr28914_19V1V3_R1.fastq.gz
zr28914_19V1V3_R2.fastq.gz
F28914.S001
original sample ID here
zr28914_1V1V3_R1.fastq.gz
zr28914_1V1V3_R2.fastq.gz
F28914.S200
original sample ID here
zr28914_200V1V3_R1.fastq.gz
zr28914_200V1V3_R2.fastq.gz
F28914.S201
original sample ID here
zr28914_201V1V3_R1.fastq.gz
zr28914_201V1V3_R2.fastq.gz
F28914.S202
original sample ID here
zr28914_202V1V3_R1.fastq.gz
zr28914_202V1V3_R2.fastq.gz
F28914.S203
original sample ID here
zr28914_203V1V3_R1.fastq.gz
zr28914_203V1V3_R2.fastq.gz
F28914.S204
original sample ID here
zr28914_204V1V3_R1.fastq.gz
zr28914_204V1V3_R2.fastq.gz
F28914.S205
original sample ID here
zr28914_205V1V3_R1.fastq.gz
zr28914_205V1V3_R2.fastq.gz
F28914.S206
original sample ID here
zr28914_206V1V3_R1.fastq.gz
zr28914_206V1V3_R2.fastq.gz
F28914.S207
original sample ID here
zr28914_207V1V3_R1.fastq.gz
zr28914_207V1V3_R2.fastq.gz
F28914.S208
original sample ID here
zr28914_208V1V3_R1.fastq.gz
zr28914_208V1V3_R2.fastq.gz
F28914.S209
original sample ID here
zr28914_209V1V3_R1.fastq.gz
zr28914_209V1V3_R2.fastq.gz
F28914.S020
original sample ID here
zr28914_20V1V3_R1.fastq.gz
zr28914_20V1V3_R2.fastq.gz
F28914.S210
original sample ID here
zr28914_210V1V3_R1.fastq.gz
zr28914_210V1V3_R2.fastq.gz
F28914.S211
original sample ID here
zr28914_211V1V3_R1.fastq.gz
zr28914_211V1V3_R2.fastq.gz
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F28914.S214
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F28914.S215
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F28914.S216
original sample ID here
zr28914_216V1V3_R1.fastq.gz
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F28914.S217
original sample ID here
zr28914_217V1V3_R1.fastq.gz
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F28914.S218
original sample ID here
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F28914.S219
original sample ID here
zr28914_219V1V3_R1.fastq.gz
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F28914.S021
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zr28914_21V1V3_R1.fastq.gz
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F28914.S220
original sample ID here
zr28914_220V1V3_R1.fastq.gz
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F28914.S221
original sample ID here
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F28914.S222
original sample ID here
zr28914_222V1V3_R1.fastq.gz
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F28914.S223
original sample ID here
zr28914_223V1V3_R1.fastq.gz
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F28914.S224
original sample ID here
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F28914.S225
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F28914.S226
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F28914.S227
original sample ID here
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F28914.S228
original sample ID here
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F28914.S229
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zr28914_229V1V3_R1.fastq.gz
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F28914.S022
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zr28914_22V1V3_R1.fastq.gz
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F28914.S230
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zr28914_230V1V3_R1.fastq.gz
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F28914.S231
original sample ID here
zr28914_231V1V3_R1.fastq.gz
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F28914.S232
original sample ID here
zr28914_232V1V3_R1.fastq.gz
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F28914.S233
original sample ID here
zr28914_233V1V3_R1.fastq.gz
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F28914.S234
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zr28914_234V1V3_R1.fastq.gz
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F28914.S235
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zr28914_235V1V3_R1.fastq.gz
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F28914.S236
original sample ID here
zr28914_236V1V3_R1.fastq.gz
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F28914.S237
original sample ID here
zr28914_237V1V3_R1.fastq.gz
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F28914.S238
original sample ID here
zr28914_238V1V3_R1.fastq.gz
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F28914.S239
original sample ID here
zr28914_239V1V3_R1.fastq.gz
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F28914.S023
original sample ID here
zr28914_23V1V3_R1.fastq.gz
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F28914.S240
original sample ID here
zr28914_240V1V3_R1.fastq.gz
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F28914.S241
original sample ID here
zr28914_241V1V3_R1.fastq.gz
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F28914.S242
original sample ID here
zr28914_242V1V3_R1.fastq.gz
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F28914.S243
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zr28914_243V1V3_R1.fastq.gz
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F28914.S244
original sample ID here
zr28914_244V1V3_R1.fastq.gz
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F28914.S245
original sample ID here
zr28914_245V1V3_R1.fastq.gz
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F28914.S246
original sample ID here
zr28914_246V1V3_R1.fastq.gz
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F28914.S247
original sample ID here
zr28914_247V1V3_R1.fastq.gz
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F28914.S248
original sample ID here
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F28914.S249
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zr28914_249V1V3_R1.fastq.gz
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F28914.S024
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F28914.S250
original sample ID here
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F28914.S251
original sample ID here
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F28914.S252
original sample ID here
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F28914.S253
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F28914.S254
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F28914.S255
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F28914.S256
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F28914.S257
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F28914.S258
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F28914.S259
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F28914.S025
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F28914.S260
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zr28914_260V1V3_R1.fastq.gz
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F28914.S261
original sample ID here
zr28914_261V1V3_R1.fastq.gz
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F28914.S262
original sample ID here
zr28914_262V1V3_R1.fastq.gz
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F28914.S263
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F28914.S264
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F28914.S265
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F28914.S266
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F28914.S267
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F28914.S268
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F28914.S269
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F28914.S026
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F28914.S270
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zr28914_270V1V3_R1.fastq.gz
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F28914.S271
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zr28914_271V1V3_R1.fastq.gz
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F28914.S272
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F28914.S273
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F28914.S274
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F28914.S275
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F28914.S276
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F28914.S277
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F28914.S278
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F28914.S279
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F28914.S027
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F28914.S280
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F28914.S281
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F28914.S282
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F28914.S283
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F28914.S285
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F28914.S286
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F28914.S287
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F28914.S288
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F28914.S289
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F28914.S028
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F28914.S290
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F28914.S291
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F28914.S292
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F28914.S293
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F28914.S294
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F28914.S002
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F28914.S300
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F28914.S305
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F28914.S310
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F28914.S311
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F28914.S312
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F28914.S313
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F28914.S315
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F28914.S316
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F28914.S031
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F28914.S322
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F28914.S324
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F28914.S325
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F28914.S326
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F28914.S329
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F28914.S032
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F28914.S330
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F28914.S335
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F28914.S336
original sample ID here
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F28914.S337
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F28914.S339
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original sample ID here
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F28914.S349
original sample ID here
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F28914.S034
original sample ID here
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F28914.S350
original sample ID here
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original sample ID here
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F28914.S352
original sample ID here
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F28914.S353
original sample ID here
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F28914.S495
original sample ID here
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original sample ID here
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original sample ID here
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F28914.S498
original sample ID here
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F28914.S499
original sample ID here
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F28914.S049
original sample ID here
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F28914.S004
original sample ID here
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F28914.S500
original sample ID here
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F28914.S501
original sample ID here
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F28914.S502
original sample ID here
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F28914.S503
original sample ID here
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F28914.S504
original sample ID here
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F28914.S505
original sample ID here
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F28914.S506
original sample ID here
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F28914.S507
original sample ID here
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F28914.S508
original sample ID here
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F28914.S509
original sample ID here
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F28914.S050
original sample ID here
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F28914.S510
original sample ID here
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F28914.S511
original sample ID here
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F28914.S512
original sample ID here
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F28914.S513
original sample ID here
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F28914.S514
original sample ID here
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F28914.S515
original sample ID here
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F28914.S516
original sample ID here
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F28914.S517
original sample ID here
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F28914.S518
original sample ID here
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F28914.S519
original sample ID here
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F28914.S051
original sample ID here
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F28914.S520
original sample ID here
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F28914.S521
original sample ID here
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F28914.S522
original sample ID here
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F28914.S523
original sample ID here
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F28914.S524
original sample ID here
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F28914.S525
original sample ID here
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F28914.S526
original sample ID here
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F28914.S527
original sample ID here
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F28914.S528
original sample ID here
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F28914.S529
original sample ID here
zr28914_529V1V3_R1.fastq.gz
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F28914.S052
original sample ID here
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F28914.S530
original sample ID here
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F28914.S531
original sample ID here
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original sample ID here
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F28914.S533
original sample ID here
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F28914.S534
original sample ID here
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F28914.S535
original sample ID here
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F28914.S536
original sample ID here
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F28914.S537
original sample ID here
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F28914.S538
original sample ID here
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F28914.S539
original sample ID here
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F28914.S053
original sample ID here
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F28914.S540
original sample ID here
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F28914.S541
original sample ID here
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F28914.S542
original sample ID here
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F28914.S543
original sample ID here
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F28914.S544
original sample ID here
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F28914.S545
original sample ID here
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F28914.S546
original sample ID here
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F28914.S547
original sample ID here
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F28914.S548
original sample ID here
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F28914.S549
original sample ID here
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F28914.S054
original sample ID here
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F28914.S550
original sample ID here
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F28914.S551
original sample ID here
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F28914.S552
original sample ID here
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F28914.S553
original sample ID here
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F28914.S554
original sample ID here
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F28914.S555
original sample ID here
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F28914.S556
original sample ID here
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F28914.S557
original sample ID here
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F28914.S558
original sample ID here
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F28914.S559
original sample ID here
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F28914.S055
original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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F28914.S564
original sample ID here
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F28914.S565
original sample ID here
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F28914.S566
original sample ID here
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F28914.S567
original sample ID here
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F28914.S568
original sample ID here
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F28914.S569
original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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F28914.S574
original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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F28914.S612
original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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F28914.S616
original sample ID here
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F28914.S617
original sample ID here
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original sample ID here
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F28914.S619
original sample ID here
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F28914.S061
original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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original sample ID here
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F28914.S629
original sample ID here
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F28914.S062
original sample ID here
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F28914.S630
original sample ID here
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F28914.S631
original sample ID here
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F28914.S632
original sample ID here
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F28914.S633
original sample ID here
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F28914.S634
original sample ID here
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F28914.S635
original sample ID here
zr28914_635V1V3_R1.fastq.gz
zr28914_635V1V3_R2.fastq.gz
F28914.S636
original sample ID here
zr28914_636V1V3_R1.fastq.gz
zr28914_636V1V3_R2.fastq.gz
F28914.S637
original sample ID here
zr28914_637V1V3_R1.fastq.gz
zr28914_637V1V3_R2.fastq.gz
F28914.S638
original sample ID here
zr28914_638V1V3_R1.fastq.gz
zr28914_638V1V3_R2.fastq.gz
F28914.S639
original sample ID here
zr28914_639V1V3_R1.fastq.gz
zr28914_639V1V3_R2.fastq.gz
F28914.S063
original sample ID here
zr28914_63V1V3_R1.fastq.gz
zr28914_63V1V3_R2.fastq.gz
F28914.S640
original sample ID here
zr28914_640V1V3_R1.fastq.gz
zr28914_640V1V3_R2.fastq.gz
F28914.S641
original sample ID here
zr28914_641V1V3_R1.fastq.gz
zr28914_641V1V3_R2.fastq.gz
F28914.S642
original sample ID here
zr28914_642V1V3_R1.fastq.gz
zr28914_642V1V3_R2.fastq.gz
F28914.S643
original sample ID here
zr28914_643V1V3_R1.fastq.gz
zr28914_643V1V3_R2.fastq.gz
F28914.S644
original sample ID here
zr28914_644V1V3_R1.fastq.gz
zr28914_644V1V3_R2.fastq.gz
F28914.S645
original sample ID here
zr28914_645V1V3_R1.fastq.gz
zr28914_645V1V3_R2.fastq.gz
F28914.S646
original sample ID here
zr28914_646V1V3_R1.fastq.gz
zr28914_646V1V3_R2.fastq.gz
F28914.S647
original sample ID here
zr28914_647V1V3_R1.fastq.gz
zr28914_647V1V3_R2.fastq.gz
F28914.S648
original sample ID here
zr28914_648V1V3_R1.fastq.gz
zr28914_648V1V3_R2.fastq.gz
F28914.S649
original sample ID here
zr28914_649V1V3_R1.fastq.gz
zr28914_649V1V3_R2.fastq.gz
F28914.S064
original sample ID here
zr28914_64V1V3_R1.fastq.gz
zr28914_64V1V3_R2.fastq.gz
F28914.S650
original sample ID here
zr28914_650V1V3_R1.fastq.gz
zr28914_650V1V3_R2.fastq.gz
F28914.S651
original sample ID here
zr28914_651V1V3_R1.fastq.gz
zr28914_651V1V3_R2.fastq.gz
F28914.S652
original sample ID here
zr28914_652V1V3_R1.fastq.gz
zr28914_652V1V3_R2.fastq.gz
F28914.S653
original sample ID here
zr28914_653V1V3_R1.fastq.gz
zr28914_653V1V3_R2.fastq.gz
F28914.S654
original sample ID here
zr28914_654V1V3_R1.fastq.gz
zr28914_654V1V3_R2.fastq.gz
F28914.S655
original sample ID here
zr28914_655V1V3_R1.fastq.gz
zr28914_655V1V3_R2.fastq.gz
F28914.S656
original sample ID here
zr28914_656V1V3_R1.fastq.gz
zr28914_656V1V3_R2.fastq.gz
F28914.S657
original sample ID here
zr28914_657V1V3_R1.fastq.gz
zr28914_657V1V3_R2.fastq.gz
F28914.S658
original sample ID here
zr28914_658V1V3_R1.fastq.gz
zr28914_658V1V3_R2.fastq.gz
F28914.S659
original sample ID here
zr28914_659V1V3_R1.fastq.gz
zr28914_659V1V3_R2.fastq.gz
F28914.S065
original sample ID here
zr28914_65V1V3_R1.fastq.gz
zr28914_65V1V3_R2.fastq.gz
F28914.S660
original sample ID here
zr28914_660V1V3_R1.fastq.gz
zr28914_660V1V3_R2.fastq.gz
F28914.S661
original sample ID here
zr28914_661V1V3_R1.fastq.gz
zr28914_661V1V3_R2.fastq.gz
F28914.S662
original sample ID here
zr28914_662V1V3_R1.fastq.gz
zr28914_662V1V3_R2.fastq.gz
F28914.S663
original sample ID here
zr28914_663V1V3_R1.fastq.gz
zr28914_663V1V3_R2.fastq.gz
F28914.S664
original sample ID here
zr28914_664V1V3_R1.fastq.gz
zr28914_664V1V3_R2.fastq.gz
F28914.S665
original sample ID here
zr28914_665V1V3_R1.fastq.gz
zr28914_665V1V3_R2.fastq.gz
F28914.S666
original sample ID here
zr28914_666V1V3_R1.fastq.gz
zr28914_666V1V3_R2.fastq.gz
F28914.S667
original sample ID here
zr28914_667V1V3_R1.fastq.gz
zr28914_667V1V3_R2.fastq.gz
F28914.S668
original sample ID here
zr28914_668V1V3_R1.fastq.gz
zr28914_668V1V3_R2.fastq.gz
F28914.S669
original sample ID here
zr28914_669V1V3_R1.fastq.gz
zr28914_669V1V3_R2.fastq.gz
F28914.S066
original sample ID here
zr28914_66V1V3_R1.fastq.gz
zr28914_66V1V3_R2.fastq.gz
F28914.S670
original sample ID here
zr28914_670V1V3_R1.fastq.gz
zr28914_670V1V3_R2.fastq.gz
F28914.S671
original sample ID here
zr28914_671V1V3_R1.fastq.gz
zr28914_671V1V3_R2.fastq.gz
F28914.S672
original sample ID here
zr28914_672V1V3_R1.fastq.gz
zr28914_672V1V3_R2.fastq.gz
F28914.S067
original sample ID here
zr28914_67V1V3_R1.fastq.gz
zr28914_67V1V3_R2.fastq.gz
F28914.S068
original sample ID here
zr28914_68V1V3_R1.fastq.gz
zr28914_68V1V3_R2.fastq.gz
F28914.S069
original sample ID here
zr28914_69V1V3_R1.fastq.gz
zr28914_69V1V3_R2.fastq.gz
F28914.S006
original sample ID here
zr28914_6V1V3_R1.fastq.gz
zr28914_6V1V3_R2.fastq.gz
F28914.S070
original sample ID here
zr28914_70V1V3_R1.fastq.gz
zr28914_70V1V3_R2.fastq.gz
F28914.S071
original sample ID here
zr28914_71V1V3_R1.fastq.gz
zr28914_71V1V3_R2.fastq.gz
F28914.S072
original sample ID here
zr28914_72V1V3_R1.fastq.gz
zr28914_72V1V3_R2.fastq.gz
F28914.S073
original sample ID here
zr28914_73V1V3_R1.fastq.gz
zr28914_73V1V3_R2.fastq.gz
F28914.S074
original sample ID here
zr28914_74V1V3_R1.fastq.gz
zr28914_74V1V3_R2.fastq.gz
F28914.S075
original sample ID here
zr28914_75V1V3_R1.fastq.gz
zr28914_75V1V3_R2.fastq.gz
F28914.S076
original sample ID here
zr28914_76V1V3_R1.fastq.gz
zr28914_76V1V3_R2.fastq.gz
F28914.S077
original sample ID here
zr28914_77V1V3_R1.fastq.gz
zr28914_77V1V3_R2.fastq.gz
F28914.S078
original sample ID here
zr28914_78V1V3_R1.fastq.gz
zr28914_78V1V3_R2.fastq.gz
F28914.S079
original sample ID here
zr28914_79V1V3_R1.fastq.gz
zr28914_79V1V3_R2.fastq.gz
F28914.S007
original sample ID here
zr28914_7V1V3_R1.fastq.gz
zr28914_7V1V3_R2.fastq.gz
F28914.S080
original sample ID here
zr28914_80V1V3_R1.fastq.gz
zr28914_80V1V3_R2.fastq.gz
F28914.S081
original sample ID here
zr28914_81V1V3_R1.fastq.gz
zr28914_81V1V3_R2.fastq.gz
F28914.S082
original sample ID here
zr28914_82V1V3_R1.fastq.gz
zr28914_82V1V3_R2.fastq.gz
F28914.S083
original sample ID here
zr28914_83V1V3_R1.fastq.gz
zr28914_83V1V3_R2.fastq.gz
F28914.S084
original sample ID here
zr28914_84V1V3_R1.fastq.gz
zr28914_84V1V3_R2.fastq.gz
F28914.S085
original sample ID here
zr28914_85V1V3_R1.fastq.gz
zr28914_85V1V3_R2.fastq.gz
F28914.S086
original sample ID here
zr28914_86V1V3_R1.fastq.gz
zr28914_86V1V3_R2.fastq.gz
F28914.S087
original sample ID here
zr28914_87V1V3_R1.fastq.gz
zr28914_87V1V3_R2.fastq.gz
F28914.S088
original sample ID here
zr28914_88V1V3_R1.fastq.gz
zr28914_88V1V3_R2.fastq.gz
F28914.S089
original sample ID here
zr28914_89V1V3_R1.fastq.gz
zr28914_89V1V3_R2.fastq.gz
F28914.S008
original sample ID here
zr28914_8V1V3_R1.fastq.gz
zr28914_8V1V3_R2.fastq.gz
F28914.S090
original sample ID here
zr28914_90V1V3_R1.fastq.gz
zr28914_90V1V3_R2.fastq.gz
F28914.S091
original sample ID here
zr28914_91V1V3_R1.fastq.gz
zr28914_91V1V3_R2.fastq.gz
F28914.S092
original sample ID here
zr28914_92V1V3_R1.fastq.gz
zr28914_92V1V3_R2.fastq.gz
F28914.S093
original sample ID here
zr28914_93V1V3_R1.fastq.gz
zr28914_93V1V3_R2.fastq.gz
F28914.S094
original sample ID here
zr28914_94V1V3_R1.fastq.gz
zr28914_94V1V3_R2.fastq.gz
F28914.S095
original sample ID here
zr28914_95V1V3_R1.fastq.gz
zr28914_95V1V3_R2.fastq.gz
F28914.S096
original sample ID here
zr28914_96V1V3_R1.fastq.gz
zr28914_96V1V3_R2.fastq.gz
F28914.S097
original sample ID here
zr28914_97V1V3_R1.fastq.gz
zr28914_97V1V3_R2.fastq.gz
F28914.S098
original sample ID here
zr28914_98V1V3_R1.fastq.gz
zr28914_98V1V3_R2.fastq.gz
F28914.S099
original sample ID here
zr28914_99V1V3_R1.fastq.gz
zr28914_99V1V3_R2.fastq.gz
F28914.S009
original sample ID here
zr28914_9V1V3_R1.fastq.gz
zr28914_9V1V3_R2.fastq.gz
Please download and save the file to your computer storage device. The download link will expire after 60 days upon your receiving of this report.
DADA2 is a software package that models and corrects Illumina-sequenced amplicon errors [1].
DADA2 infers sample sequences exactly, without coarse-graining into OTUs,
and resolves differences of as little as one nucleotide. DADA2 identified more real variants
and output fewer spurious sequences than other methods.
DADA2’s advantage is that it uses more of the data. The DADA2 error model incorporates quality information,
which is ignored by all other methods after filtering. The DADA2 error model incorporates quantitative abundances,
whereas most other methods use abundance ranks if they use abundance at all.
The DADA2 error model identifies the differences between sequences, eg. A->C,
whereas other methods merely count the mismatches. DADA2 can parameterize its error model from the data itself,
rather than relying on previous datasets that may or may not reflect the PCR and sequencing protocols used in your study.
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016 Jul;13(7):581-3. doi: 10.1038/nmeth.3869. Epub 2016 May 23. PMID: 27214047; PMCID: PMC4927377.
Analysis Procedures:
DADA2 pipeline includes several tools for read quality control, including quality filtering, trimming, denoising, pair merging and chimera filtering. Below are the major processing steps of DADA2:
Step 1. Read trimming based on sequence quality
The quality of NGS Illumina sequences often decreases toward the end of the reads.
DADA2 allows to trim off the poor quality read ends in order to improve the error
model building and pair mergicing performance.
Step 2. Learn the Error Rates
The DADA2 algorithm makes use of a parametric error model (err) and every
amplicon dataset has a different set of error rates. The learnErrors method
learns this error model from the data, by alternating estimation of the error
rates and inference of sample composition until they converge on a jointly
consistent solution. As in many machine-learning problems, the algorithm must
begin with an initial guess, for which the maximum possible error rates in
this data are used (the error rates if only the most abundant sequence is
correct and all the rest are errors).
Step 3. Infer amplicon sequence variants (ASVs) based on the error model built in previous step. This step is also called sequence "denoising".
The outcome of this step is a list of ASVs that are the equivalent of oligonucleotides.
Step 4. Merge paired reads. If the sequencing products are read pairs, DADA2 will merge the R1 and R2 ASVs into single sequences.
Merging is performed by aligning the denoised forward reads with the reverse-complement of the corresponding
denoised reverse reads, and then constructing the merged “contig” sequences.
By default, merged sequences are only output if the forward and reverse reads overlap by
at least 12 bases, and are identical to each other in the overlap region (but these conditions can be changed via function arguments).
Step 5. Remove chimera.
The core dada method corrects substitution and indel errors, but chimeras remain. Fortunately, the accuracy of sequence variants
after denoising makes identifying chimeric ASVs simpler than when dealing with fuzzy OTUs.
Chimeric sequences are identified if they can be exactly reconstructed by
combining a left-segment and a right-segment from two more abundant “parent” sequences. The frequency of chimeric sequences varies substantially
from dataset to dataset, and depends on on factors including experimental procedures and sample complexity.
Results
1. Read Quality Plots NGS sequence analaysis starts with visualizing the quality of the sequencing. Below are the quality plots of the first
sample for the R1 and R2 reads separately. In gray-scale is a heat map of the frequency of each quality score at each base position. The mean
quality score at each position is shown by the green line, and the quartiles of the quality score distribution by the orange lines.
The forward reads are usually of better quality. It is a common practice to trim the last few nucleotides to avoid less well-controlled errors
that can arise there. The trimming affects the downstream steps including error model building, merging and chimera calling. FOMC uses an empirical
approach to test many combinations of different trim length in order to achieve best final amplicon sequence variants (ASVs), see the next
section “Optimal trim length for ASVs”.
2. Optimal trim length for ASVs The final number of merged and chimera-filtered ASVs depends on the quality filtering (hence trimming) in the very beginning of the DADA2 pipeline.
In order to achieve highest number of ASVs, an empirical approach was used -
Create a random subset of each sample consisting of 5,000 R1 and 5,000 R2 (to reduce computation time)
Trim 10 bases at a time from the ends of both R1 and R2 up to 50 bases
For each combination of trimmed length (e.g., 300x300, 300x290, 290x290 etc), the trimmed reads are
subject to the entire DADA2 pipeline for chimera-filtered merged ASVs
The combination with highest percentage of the input reads becoming final ASVs is selected for the complete set of data
Below is the result of such operation, showing ASV percentages of total reads for all trimming combinations (1st Column = R1 lengths in bases; 1st Row = R2 lengths in bases):
R1/R2
301
291
281
271
261
251
301
80.38%
81.81%
81.75%
81.95%
82.16%
70.85%
291
80.43%
81.88%
81.75%
82.01%
70.55%
57.91%
281
80.61%
81.99%
81.92%
70.29%
57.79%
4.52%
271
80.78%
82.28%
70.46%
57.73%
4.51%
3.47%
261
80.88%
70.62%
57.81%
4.55%
3.46%
2.56%
251
69.57%
58.27%
4.57%
3.48%
2.56%
1.79%
Based on the above result, the trim length combination of R1 = 271 bases and R2 = 291 bases (highlighted red above), was chosen for generating final ASVs for all sequences.
This combination generated highest number of merged non-chimeric ASVs and was used for downstream analyses, if requested.
3. Error plots from learning the error rates
After DADA2 building the error model for the set of data, it is always worthwhile, as a sanity check if nothing else, to visualize the estimated error rates.
The error rates for each possible transition (A→C, A→G, …) are shown below. Points are the observed error rates for each consensus quality score.
The black line shows the estimated error rates after convergence of the machine-learning algorithm.
The red line shows the error rates expected under the nominal definition of the Q-score.
The ideal result would be the estimated error rates (black line) are a good fit to the observed rates (points), and the error rates drop
with increased quality as expected.
Forward Read R1 Error Plot
Reverse Read R2 Error Plot
The PDF version of these plots are available here:
4. DADA2 Result Summary The table below shows the summary of the DADA2 analysis,
tracking paired read counts of each samples for all the steps during DADA2 denoising process -
including end-trimming (filtered), denoising (denoisedF, denoisedF), pair merging (merged) and chimera removal (nonchim).
Sample ID
F28914.S001
F28914.S002
F28914.S003
F28914.S004
F28914.S005
F28914.S006
F28914.S007
F28914.S008
F28914.S009
F28914.S010
F28914.S011
F28914.S012
F28914.S013
F28914.S014
F28914.S015
F28914.S016
F28914.S017
F28914.S018
F28914.S019
F28914.S020
F28914.S021
F28914.S022
F28914.S023
F28914.S024
F28914.S025
F28914.S026
F28914.S027
F28914.S028
F28914.S029
F28914.S030
F28914.S031
F28914.S032
F28914.S033
F28914.S034
F28914.S035
F28914.S036
F28914.S037
F28914.S038
F28914.S039
F28914.S040
F28914.S041
F28914.S042
F28914.S043
F28914.S044
F28914.S045
F28914.S046
F28914.S047
F28914.S048
F28914.S049
F28914.S050
F28914.S051
F28914.S052
F28914.S053
F28914.S054
F28914.S055
F28914.S056
F28914.S057
F28914.S058
F28914.S059
F28914.S060
F28914.S061
F28914.S062
F28914.S063
F28914.S064
F28914.S065
F28914.S066
F28914.S067
F28914.S068
F28914.S069
F28914.S070
F28914.S071
F28914.S072
F28914.S073
F28914.S074
F28914.S075
F28914.S076
F28914.S077
F28914.S078
F28914.S079
F28914.S080
F28914.S081
F28914.S082
F28914.S083
F28914.S084
F28914.S085
F28914.S086
F28914.S087
F28914.S088
F28914.S089
F28914.S090
F28914.S091
F28914.S092
F28914.S093
F28914.S094
F28914.S095
F28914.S096
F28914.S097
F28914.S098
F28914.S099
F28914.S100
F28914.S101
F28914.S102
F28914.S103
F28914.S104
F28914.S105
F28914.S106
F28914.S107
F28914.S108
F28914.S109
F28914.S110
F28914.S111
F28914.S112
F28914.S113
F28914.S114
F28914.S115
F28914.S116
F28914.S117
F28914.S118
F28914.S119
F28914.S120
F28914.S121
F28914.S122
F28914.S123
F28914.S124
F28914.S125
F28914.S126
F28914.S127
F28914.S128
F28914.S129
F28914.S130
F28914.S131
F28914.S132
F28914.S133
F28914.S134
F28914.S135
F28914.S136
F28914.S137
F28914.S138
F28914.S139
F28914.S140
F28914.S141
F28914.S142
F28914.S143
F28914.S144
F28914.S145
F28914.S146
F28914.S147
F28914.S148
F28914.S149
F28914.S150
F28914.S151
F28914.S152
F28914.S153
F28914.S154
F28914.S155
F28914.S156
F28914.S157
F28914.S158
F28914.S159
F28914.S160
F28914.S161
F28914.S162
F28914.S163
F28914.S164
F28914.S165
F28914.S166
F28914.S167
F28914.S168
F28914.S169
F28914.S170
F28914.S171
F28914.S172
F28914.S173
F28914.S174
F28914.S175
F28914.S176
F28914.S177
F28914.S178
F28914.S179
F28914.S180
F28914.S181
F28914.S182
F28914.S183
F28914.S184
F28914.S185
F28914.S186
F28914.S187
F28914.S188
F28914.S189
F28914.S190
F28914.S191
F28914.S192
F28914.S193
F28914.S194
F28914.S195
F28914.S196
F28914.S197
F28914.S198
F28914.S199
F28914.S200
F28914.S201
F28914.S202
F28914.S203
F28914.S204
F28914.S205
F28914.S206
F28914.S207
F28914.S208
F28914.S209
F28914.S210
F28914.S211
F28914.S212
F28914.S213
F28914.S214
F28914.S215
F28914.S216
F28914.S217
F28914.S218
F28914.S219
F28914.S220
F28914.S221
F28914.S222
F28914.S223
F28914.S224
F28914.S225
F28914.S226
F28914.S227
F28914.S228
F28914.S229
F28914.S230
F28914.S231
F28914.S232
F28914.S233
F28914.S234
F28914.S235
F28914.S236
F28914.S237
F28914.S238
F28914.S239
F28914.S240
F28914.S241
F28914.S242
F28914.S243
F28914.S244
F28914.S245
F28914.S246
F28914.S247
F28914.S248
F28914.S249
F28914.S250
F28914.S251
F28914.S252
F28914.S253
F28914.S254
F28914.S255
F28914.S256
F28914.S257
F28914.S258
F28914.S259
F28914.S260
F28914.S261
F28914.S262
F28914.S263
F28914.S264
F28914.S265
F28914.S266
F28914.S267
F28914.S268
F28914.S269
F28914.S270
F28914.S271
F28914.S272
F28914.S273
F28914.S274
F28914.S275
F28914.S276
F28914.S277
F28914.S278
F28914.S279
F28914.S280
F28914.S281
F28914.S282
F28914.S283
F28914.S284
F28914.S285
F28914.S286
F28914.S287
F28914.S288
F28914.S289
F28914.S290
F28914.S291
F28914.S292
F28914.S293
F28914.S294
F28914.S295
F28914.S296
F28914.S297
F28914.S300
F28914.S301
F28914.S302
F28914.S303
F28914.S304
F28914.S305
F28914.S306
F28914.S307
F28914.S308
F28914.S309
F28914.S310
F28914.S311
F28914.S312
F28914.S313
F28914.S314
F28914.S315
F28914.S316
F28914.S317
F28914.S318
F28914.S319
F28914.S320
F28914.S321
F28914.S322
F28914.S323
F28914.S324
F28914.S325
F28914.S326
F28914.S327
F28914.S328
F28914.S329
F28914.S330
F28914.S331
F28914.S332
F28914.S333
F28914.S334
F28914.S335
F28914.S336
F28914.S337
F28914.S338
F28914.S339
F28914.S340
F28914.S341
F28914.S342
F28914.S343
F28914.S344
F28914.S345
F28914.S346
F28914.S347
F28914.S348
F28914.S349
F28914.S350
F28914.S351
F28914.S352
F28914.S353
F28914.S354
F28914.S355
F28914.S356
F28914.S357
F28914.S358
F28914.S359
F28914.S360
F28914.S361
F28914.S362
F28914.S363
F28914.S364
F28914.S365
F28914.S366
F28914.S367
F28914.S368
F28914.S369
F28914.S370
F28914.S371
F28914.S372
F28914.S373
F28914.S374
F28914.S375
F28914.S376
F28914.S377
F28914.S378
F28914.S379
F28914.S380
F28914.S381
F28914.S382
F28914.S383
F28914.S384
F28914.S385
F28914.S386
F28914.S387
F28914.S388
F28914.S389
F28914.S390
F28914.S391
F28914.S392
F28914.S393
F28914.S394
F28914.S395
F28914.S396
F28914.S397
F28914.S398
F28914.S399
F28914.S400
F28914.S401
F28914.S402
F28914.S403
F28914.S404
F28914.S405
F28914.S406
F28914.S407
F28914.S408
F28914.S409
F28914.S410
F28914.S411
F28914.S412
F28914.S413
F28914.S414
F28914.S415
F28914.S416
F28914.S417
F28914.S418
F28914.S419
F28914.S420
F28914.S421
F28914.S422
F28914.S423
F28914.S424
F28914.S425
F28914.S426
F28914.S427
F28914.S428
F28914.S429
F28914.S430
F28914.S431
F28914.S432
F28914.S433
F28914.S434
F28914.S435
F28914.S436
F28914.S437
F28914.S438
F28914.S439
F28914.S440
F28914.S441
F28914.S442
F28914.S443
F28914.S444
F28914.S445
F28914.S446
F28914.S447
F28914.S448
F28914.S449
F28914.S450
F28914.S451
F28914.S452
F28914.S453
F28914.S454
F28914.S455
F28914.S456
F28914.S457
F28914.S458
F28914.S459
F28914.S460
F28914.S461
F28914.S462
F28914.S463
F28914.S464
F28914.S465
F28914.S466
F28914.S467
F28914.S468
F28914.S469
F28914.S470
F28914.S471
F28914.S472
F28914.S473
F28914.S474
F28914.S475
F28914.S476
F28914.S477
F28914.S478
F28914.S479
F28914.S480
F28914.S481
F28914.S482
F28914.S483
F28914.S484
F28914.S485
F28914.S486
F28914.S487
F28914.S488
F28914.S489
F28914.S490
F28914.S491
F28914.S492
F28914.S493
F28914.S494
F28914.S495
F28914.S496
F28914.S497
F28914.S498
F28914.S499
F28914.S500
F28914.S501
F28914.S502
F28914.S503
F28914.S504
F28914.S505
F28914.S506
F28914.S507
F28914.S508
F28914.S509
F28914.S510
F28914.S511
F28914.S512
F28914.S513
F28914.S514
F28914.S515
F28914.S516
F28914.S517
F28914.S518
F28914.S519
F28914.S520
F28914.S521
F28914.S522
F28914.S523
F28914.S524
F28914.S525
F28914.S526
F28914.S527
F28914.S528
F28914.S529
F28914.S530
F28914.S531
F28914.S532
F28914.S533
F28914.S534
F28914.S535
F28914.S536
F28914.S537
F28914.S538
F28914.S539
F28914.S540
F28914.S541
F28914.S542
F28914.S543
F28914.S544
F28914.S545
F28914.S546
F28914.S547
F28914.S548
F28914.S549
F28914.S550
F28914.S551
F28914.S552
F28914.S553
F28914.S554
F28914.S555
F28914.S556
F28914.S557
F28914.S558
F28914.S559
F28914.S560
F28914.S561
F28914.S562
F28914.S563
F28914.S564
F28914.S565
F28914.S566
F28914.S567
F28914.S568
F28914.S569
F28914.S570
F28914.S571
F28914.S572
F28914.S573
F28914.S574
F28914.S575
F28914.S576
F28914.S577
F28914.S578
F28914.S579
F28914.S580
F28914.S581
F28914.S582
F28914.S583
F28914.S584
F28914.S585
F28914.S586
F28914.S587
F28914.S588
F28914.S589
F28914.S590
F28914.S591
F28914.S592
F28914.S593
F28914.S594
F28914.S595
F28914.S596
F28914.S597
F28914.S598
F28914.S599
F28914.S600
F28914.S601
F28914.S602
F28914.S603
F28914.S604
F28914.S605
F28914.S606
F28914.S607
F28914.S608
F28914.S609
F28914.S610
F28914.S611
F28914.S612
F28914.S613
F28914.S614
F28914.S615
F28914.S616
F28914.S617
F28914.S618
F28914.S619
F28914.S620
F28914.S621
F28914.S622
F28914.S623
F28914.S624
F28914.S625
F28914.S626
F28914.S627
F28914.S628
F28914.S629
F28914.S630
F28914.S631
F28914.S632
F28914.S633
F28914.S634
F28914.S635
F28914.S636
F28914.S637
F28914.S638
F28914.S639
F28914.S640
F28914.S641
F28914.S642
F28914.S643
F28914.S644
F28914.S645
F28914.S646
F28914.S647
F28914.S648
F28914.S649
F28914.S650
F28914.S651
F28914.S652
F28914.S653
F28914.S654
F28914.S655
F28914.S656
F28914.S657
F28914.S658
F28914.S659
F28914.S660
F28914.S661
F28914.S662
F28914.S663
F28914.S664
F28914.S665
F28914.S666
F28914.S667
F28914.S668
F28914.S669
F28914.S670
F28914.S671
F28914.S672
Row Sum
Percentage
input
58,906
92,674
85,550
47,257
62,302
66,421
75,034
74,306
66,556
73,327
81,811
69,437
61,867
47,217
70,069
62,535
62,202
56,479
65,136
69,928
68,690
74,019
59,127
69,327
54,222
87,994
72,273
72,044
85,075
66,823
68,972
70,306
69,146
67,967
72,715
72,665
74,123
65,239
79,089
65,194
86,177
66,482
78,290
86,172
101,765
88,967
59,342
63,476
84,713
103,322
80,559
67,621
74,417
91,839
71,408
70,095
65,068
80,611
64,568
62,990
74,960
122,030
79,250
78,653
69,591
56,489
114,581
119,302
116,615
87,989
64,089
65,807
72,015
66,767
88,578
65,559
64,100
62,064
66,845
50,040
80,078
93,554
74,947
84,802
67,901
85,344
77,142
83,561
75,690
75,566
61,493
82,753
68,648
71,761
67,901
74,463
62,991
64,533
71,072
77,830
74,528
64,598
81,124
77,112
75,231
73,111
77,151
83,749
76,712
75,608
76,159
72,585
54,755
65,094
71,558
68,309
72,161
80,489
77,874
66,601
57,582
74,071
62,624
55,002
69,910
71,713
74,783
63,360
53,546
61,366
65,533
77,015
75,240
66,242
77,796
67,577
72,349
66,848
66,840
64,508
75,113
83,432
73,063
66,804
58,905
68,641
72,778
64,677
72,827
75,968
65,584
68,845
65,323
69,984
81,418
67,050
90,546
84,515
75,563
71,927
68,910
74,016
83,541
84,577
88,489
80,681
89,412
66,776
68,979
80,685
58,758
85,931
85,553
69,811
77,835
67,453
83,559
102,386
70,274
90,406
101,138
92,202
72,689
88,582
64,147
66,667
75,169
67,162
73,843
73,661
50,662
78,616
55,339
61,710
82,758
63,611
55,537
71,459
59,419
57,990
67,454
94,127
36,723
69,811
68,326
64,411
89,079
87,127
68,227
80,377
75,065
94,248
76,687
65,349
67,563
86,413
81,341
68,403
73,848
89,555
67,871
60,849
72,351
70,801
85,528
76,318
72,983
83,967
73,261
71,649
85,921
76,985
72,841
65,225
80,898
70,965
65,346
73,225
76,566
63,331
73,904
85,662
65,552
87,053
76,906
68,889
84,243
76,059
55,751
86,895
83,269
46,195
59,845
70,424
77,608
67,709
63,163
50,390
68,156
69,734
61,938
60,165
62,175
64,436
67,603
70,906
54,415
77,980
56,715
74,368
70,496
76,343
77,402
64,533
55,406
77,222
61,802
63,731
63,232
66,043
71,434
59,856
66,301
58,954
75,786
60,848
66,244
73,491
89,661
78,023
53,763
60,491
71,399
93,675
87,937
67,031
75,626
72,848
60,986
76,891
62,537
57,868
74,285
99,893
68,375
68,403
88,384
70,035
96,717
105,401
134,287
73,211
56,334
80,071
84,045
66,616
93,172
72,725
72,129
62,980
70,277
63,193
89,324
96,145
75,930
89,543
70,812
88,682
84,962
96,588
77,921
78,749
63,524
95,988
79,947
56,004
72,264
56,388
81,624
76,526
70,761
83,986
81,794
75,813
80,665
85,054
72,464
66,413
85,839
81,133
83,139
73,542
77,381
78,908
74,670
72,654
78,842
77,432
77,097
79,101
73,906
84,113
73,902
84,105
81,969
81,033
65,909
79,436
67,449
62,817
65,003
69,251
78,059
74,163
67,317
79,905
75,892
74,757
84,321
68,543
77,690
76,440
71,276
68,350
78,405
79,862
70,365
68,754
74,025
70,988
63,640
73,005
67,909
68,393
62,485
62,102
66,976
61,203
87,027
79,909
74,997
68,633
70,476
58,253
82,906
82,495
78,572
73,401
82,843
67,932
67,269
80,869
54,876
93,243
77,108
64,120
58,957
68,656
72,425
87,047
68,113
82,229
86,901
77,238
80,269
77,805
72,610
80,318
66,293
83,884
49,681
53,012
56,768
52,311
54,871
52,864
45,233
70,159
71,579
57,863
78,052
63,016
58,678
63,606
56,703
57,729
57,177
82,451
32,021
64,485
76,451
67,536
59,505
69,771
64,999
55,860
59,288
54,756
60,505
73,708
76,708
53,487
65,034
77,087
64,387
52,343
63,782
66,007
75,337
69,913
64,997
59,027
79,399
67,325
61,820
64,362
67,958
57,292
58,420
56,864
74,128
59,385
82,938
47,202
62,079
49,224
37,598
56,274
34,370
49,597
50,348
39,108
45,908
41,816
60,106
48,979
57,509
44,220
41,037
52,905
85,090
102,322
63,105
60,970
78,555
61,534
57,872
64,428
50,483
58,636
43,634
44,105
74,222
58,741
57,459
59,258
52,237
63,831
46,802
41,357
62,075
65,815
65,157
102,385
88,569
54,495
75,757
95,589
71,482
79,114
79,475
80,701
76,740
76,467
74,528
60,244
76,039
91,321
71,002
75,459
63,402
75,004
79,895
81,636
71,733
86,072
57,882
96,439
76,098
85,414
107,361
84,355
78,570
88,535
72,321
76,877
79,310
69,855
83,860
78,348
75,053
69,792
92,114
75,338
83,018
88,189
107,400
96,309
66,688
75,186
95,959
120,079
96,844
84,168
95,073
121,142
84,803
89,738
84,460
91,191
77,132
74,859
88,983
129,843
87,470
83,582
91,942
66,462
120,731
112,632
100,424
90,063
66,900
77,001
94,058
78,589
96,637
86,041
94,534
84,228
60,434
70,499
90,447
123,885
88,638
91,986
82,570
102,924
85,240
104,527
79,293
80,835
66,353
101,871
90,229
83,368
79,570
88,899
82,326
77,274
76,725
79,758
85,292
67,906
96,210
86,951
80,184
83,610
89,856
92,472
88,898
87,031
76,292
93,200
74,289
85,098
94,218
89,705
78,341
71,806
89,841
88,495
73,490
129,527
102,111
75,450
83,364
84,256
105,754
102,784
78,837
83,286
82,056
100,945
81,855
75,540
90,513
79,147
81,898
84,604
78,581
71,038
85,660
84,473
76,595
70,052
77,632
81,660
85,008
76,211
49,718,815
100.00%
filtered
58,906
92,674
85,550
47,257
62,302
66,420
75,033
74,306
66,556
73,327
81,811
69,437
61,867
47,217
70,069
62,535
62,202
56,479
65,136
69,928
68,690
74,019
59,126
69,327
54,222
87,994
72,273
72,044
85,073
66,823
68,972
70,305
69,145
67,967
72,715
72,665
74,122
65,239
79,089
65,194
86,177
66,482
78,290
86,172
101,764
88,966
59,342
63,475
84,712
103,322
80,559
67,621
74,417
91,839
71,407
70,094
65,068
80,610
64,567
62,990
74,959
122,029
79,250
78,652
69,590
56,489
114,581
119,301
116,613
87,989
64,089
65,806
72,015
66,767
88,577
65,559
64,099
62,064
66,845
50,040
80,078
93,554
74,944
84,802
67,899
85,344
77,142
83,561
75,690
75,566
61,493
82,752
68,648
71,761
67,900
74,463
62,988
64,533
71,072
77,830
74,528
64,598
81,124
77,112
75,231
73,111
77,149
83,749
76,712
75,608
76,159
72,585
54,755
65,093
71,558
68,309
72,161
80,489
77,874
66,601
57,582
74,070
62,624
55,002
69,910
71,712
74,783
63,360
53,546
61,366
65,533
77,015
75,239
66,242
77,796
67,577
72,348
66,848
66,839
64,508
75,113
83,432
73,063
66,804
58,904
68,641
72,778
64,677
72,826
75,968
65,583
68,844
65,323
69,984
81,417
67,050
90,546
84,515
75,563
71,927
68,910
74,015
83,541
84,577
88,487
80,680
89,412
66,776
68,979
80,685
58,758
85,931
85,552
69,810
77,833
67,453
83,559
102,384
70,274
90,406
101,138
92,202
72,689
88,582
64,147
66,667
75,169
67,161
73,843
73,661
50,662
78,616
55,339
61,709
82,756
63,611
55,537
71,459
59,418
57,990
67,453
94,127
36,722
69,811
68,325
64,411
89,078
87,127
68,227
80,376
75,064
94,246
76,687
65,349
67,561
86,413
81,341
68,403
73,846
89,555
67,871
60,849
72,351
70,801
85,525
76,318
72,983
83,965
73,261
71,648
85,921
76,985
72,840
65,224
80,898
70,965
65,346
73,225
76,564
63,331
73,904
85,661
65,550
87,052
76,906
68,886
84,241
76,058
55,750
86,893
83,269
46,194
59,845
70,424
77,608
67,707
63,163
50,389
68,156
69,732
61,936
60,164
62,175
64,434
67,603
70,906
54,415
77,979
56,715
74,368
70,493
76,341
77,402
64,533
55,405
77,221
61,802
63,731
63,230
66,043
71,434
59,856
66,301
58,953
75,786
60,848
66,244
73,491
89,660
78,022
53,763
60,491
71,399
93,675
87,935
67,030
75,625
72,848
60,986
76,891
62,536
57,868
74,284
99,891
68,374
68,402
88,382
70,033
96,716
105,399
134,286
73,210
56,333
80,069
84,044
66,614
93,171
72,723
72,126
62,979
70,277
63,193
89,324
96,145
75,929
89,543
70,812
88,682
84,962
96,585
77,920
78,749
63,523
95,987
79,946
56,004
72,263
56,388
81,624
76,524
70,760
83,985
81,792
75,811
80,662
85,052
72,464
66,413
85,838
81,130
83,138
73,541
77,379
78,908
74,670
72,654
78,842
77,431
77,096
79,099
73,906
84,113
73,901
84,105
81,968
81,033
65,909
79,434
67,448
62,815
65,003
69,250
78,057
74,161
67,316
79,904
75,892
74,757
84,319
68,542
77,690
76,440
71,275
68,350
78,404
79,862
70,364
68,753
74,023
70,988
63,640
73,005
67,907
68,393
62,485
62,102
66,975
61,203
87,027
79,907
74,995
68,632
70,475
58,252
82,904
82,495
78,572
73,401
82,842
67,932
67,267
80,867
54,873
93,241
77,108
64,120
58,957
68,655
72,425
87,047
68,113
82,228
86,901
77,237
80,269
77,804
72,610
80,318
66,292
83,882
49,681
53,012
56,767
52,311
54,870
52,863
45,233
70,159
71,578
57,863
78,051
63,014
58,676
63,602
56,703
57,728
57,176
82,451
32,021
64,483
76,451
67,536
59,504
69,771
64,997
55,860
59,288
54,755
60,504
73,708
76,707
53,487
65,033
77,087
64,386
52,343
63,782
66,006
75,334
69,913
64,997
59,027
79,399
67,325
61,819
64,361
67,958
57,291
58,419
56,864
74,128
59,385
82,936
47,201
62,078
49,224
37,598
56,274
34,368
49,597
50,347
39,108
45,907
41,815
60,105
48,979
57,509
44,219
41,037
52,904
85,089
102,320
63,104
60,969
78,555
61,534
57,871
64,428
50,483
58,634
43,634
44,105
74,222
58,741
57,457
59,258
52,236
63,828
46,802
41,357
62,073
65,813
65,156
102,383
88,566
54,493
75,755
95,589
71,481
79,114
79,475
80,698
76,736
76,466
74,528
60,243
76,038
91,320
71,000
75,459
63,400
75,003
79,895
81,635
71,732
86,072
57,882
96,439
76,098
85,414
107,359
84,355
78,570
88,534
72,318
76,875
79,310
69,853
83,859
78,348
75,051
69,791
92,112
75,336
83,018
88,187
107,400
96,308
66,687
75,184
95,958
120,079
96,843
84,163
95,072
121,138
84,802
89,737
84,460
91,189
77,130
74,859
88,983
129,842
87,468
83,582
91,941
66,461
120,728
112,631
100,422
90,063
66,899
77,000
94,057
78,585
96,636
86,040
94,534
84,226
60,433
70,499
90,446
123,883
88,637
91,986
82,569
102,923
85,238
104,526
79,291
80,835
66,350
101,870
90,229
83,368
79,569
88,897
82,326
77,274
76,725
79,757
85,291
67,904
96,207
86,951
80,184
83,608
89,856
92,470
88,896
87,029
76,292
93,199
74,288
85,098
94,217
89,704
78,340
71,804
89,839
88,494
73,489
129,525
102,111
75,448
83,363
84,255
105,754
102,784
78,836
83,286
82,054
100,943
81,854
75,539
90,511
79,146
81,896
84,603
78,581
71,038
85,660
84,473
76,594
70,052
77,631
81,658
85,007
76,211
49,718,349
100.00%
denoisedF
57,828
91,544
84,311
46,477
61,105
65,357
73,877
73,374
65,681
72,347
80,515
68,261
61,038
46,413
68,729
61,491
61,305
55,511
64,185
69,025
67,700
72,789
58,422
68,462
53,832
87,447
71,766
71,613
84,601
66,466
68,562
69,959
68,752
67,505
72,319
72,338
73,595
64,832
78,386
64,577
85,638
65,937
77,782
85,749
101,344
88,633
59,039
62,971
84,188
102,634
79,961
67,139
73,925
91,058
71,132
69,746
64,552
80,228
64,295
62,532
74,407
121,281
78,676
78,019
69,060
55,983
114,238
118,977
116,113
87,534
63,726
65,446
71,474
66,355
87,890
65,012
63,641
61,542
66,325
49,580
79,576
92,831
74,451
84,009
67,398
84,770
76,443
82,951
75,160
75,070
61,095
82,303
68,090
71,207
67,449
73,922
62,477
63,914
70,614
77,249
73,952
64,126
80,510
76,562
74,773
72,558
76,502
82,954
76,130
75,170
75,477
72,012
54,214
64,512
71,080
67,819
71,704
80,054
77,348
66,253
56,906
73,450
62,024
54,478
69,372
71,011
74,143
62,718
53,112
60,772
65,077
76,053
74,665
65,842
77,420
67,022
71,684
66,359
66,300
63,758
74,569
82,831
72,483
66,300
58,191
68,011
72,184
64,208
72,362
75,328
65,019
68,430
65,130
69,560
81,144
66,803
90,246
84,273
75,172
71,591
68,833
73,881
83,336
84,477
88,331
80,428
89,165
66,638
68,816
80,479
58,653
85,638
85,359
69,536
77,539
67,188
83,241
101,944
70,173
90,125
100,806
91,825
72,245
88,114
64,020
66,532
74,967
66,997
73,693
73,524
50,527
78,379
55,087
61,220
82,373
63,336
55,282
71,178
59,168
57,697
67,273
93,921
36,617
69,658
68,056
64,121
88,961
86,843
67,991
79,920
74,831
94,019
76,546
65,163
67,419
86,195
81,049
68,174
73,661
89,295
67,620
60,650
72,076
70,749
85,326
76,107
72,548
83,813
73,014
71,524
85,639
76,746
72,299
64,759
80,309
70,422
64,889
72,596
75,971
62,830
73,418
85,193
64,971
86,435
76,471
68,517
83,628
75,444
55,347
86,266
82,830
45,839
59,503
69,844
77,059
67,269
62,566
49,922
67,610
69,345
61,477
59,565
61,631
64,002
67,043
70,464
54,088
77,247
56,172
73,777
70,133
75,891
76,906
64,028
55,038
76,658
61,276
63,274
62,840
65,554
70,814
59,423
65,725
58,635
75,307
60,278
65,749
72,944
89,209
77,597
53,348
60,039
70,907
93,146
87,368
66,514
75,014
72,142
60,568
76,274
62,111
57,300
73,885
99,382
67,932
67,909
87,788
69,367
96,059
104,926
133,902
72,937
56,176
79,730
83,560
66,432
92,927
72,388
71,965
62,806
70,114
63,067
89,180
95,952
75,703
89,384
70,594
88,380
84,745
96,313
77,702
78,510
63,299
95,722
79,742
55,865
72,096
56,197
81,392
76,375
70,514
83,828
81,605
75,543
80,448
84,895
72,143
66,048
85,371
80,782
82,906
73,082
77,135
78,618
74,457
72,353
78,594
77,067
76,953
78,950
73,810
83,898
73,758
83,894
81,818
80,783
65,756
79,268
67,321
62,644
64,898
69,122
77,859
73,855
67,253
79,697
75,803
74,625
84,190
68,401
77,454
76,023
71,118
68,227
78,287
79,734
70,213
68,645
73,844
70,790
63,330
72,761
67,778
68,257
62,113
61,733
66,465
60,738
86,896
79,786
74,907
68,536
70,323
58,123
82,657
82,282
78,383
73,186
82,569
67,700
67,083
80,584
54,730
92,946
76,904
63,937
58,764
68,485
72,105
86,653
67,768
81,937
86,685
76,981
79,941
77,499
72,532
80,173
66,161
83,735
49,316
52,434
56,314
51,812
54,345
52,481
44,575
69,615
71,330
57,693
77,885
62,853
58,546
63,470
56,559
57,554
56,887
82,198
31,924
64,328
76,186
67,332
59,295
69,604
64,829
55,738
59,150
54,681
60,348
73,498
76,522
53,317
64,767
76,772
64,158
52,167
63,544
65,711
75,130
69,700
64,871
58,927
79,256
67,180
61,591
63,951
67,620
57,020
58,338
56,762
73,989
59,312
82,756
47,111
61,981
49,084
37,553
56,181
34,314
49,545
50,288
39,062
45,843
41,719
59,974
48,815
57,434
44,107
40,971
52,842
84,738
102,035
62,971
60,813
78,442
61,453
57,812
64,369
50,401
58,565
43,302
43,798
73,864
58,396
57,241
58,939
51,869
63,375
46,747
41,250
62,013
65,704
65,038
102,188
88,480
54,365
75,598
95,456
71,393
79,046
79,289
80,625
76,465
76,280
74,429
60,172
75,987
91,261
70,884
75,323
63,214
74,846
79,746
81,542
71,665
85,987
57,766
96,366
75,943
85,299
106,589
83,777
78,033
88,030
71,953
76,250
78,674
69,353
83,730
78,152
74,867
69,680
91,911
75,164
82,852
87,996
107,254
95,925
66,441
74,914
95,673
119,784
96,582
83,963
94,628
120,774
84,429
89,336
83,976
90,771
77,044
74,390
88,888
129,716
87,356
83,424
91,756
66,339
120,508
112,491
99,716
89,530
66,463
76,581
93,607
78,366
96,402
85,678
94,017
83,822
60,246
70,268
90,305
123,427
88,321
91,757
82,123
102,522
84,996
104,143
78,962
80,456
66,028
101,469
89,671
82,931
79,204
88,517
82,233
77,169
76,609
79,562
85,208
67,731
96,092
86,857
80,098
83,445
89,771
92,327
88,755
86,851
76,229
93,119
74,164
84,983
94,083
89,605
78,270
71,747
89,780
88,349
72,954
129,149
101,815
75,268
83,317
84,047
105,598
102,556
78,465
82,946
81,714
100,597
81,733
75,326
90,408
78,984
81,691
84,490
78,473
70,922
85,373
84,294
76,485
69,957
77,524
81,543
84,838
76,071
49,489,052
99.54%
denoisedR
57,195
90,076
83,283
45,812
60,634
64,336
73,558
72,660
64,925
71,758
80,051
67,849
60,326
45,807
68,461
61,048
60,638
54,801
63,754
68,343
67,078
72,427
57,782
67,808
53,532
86,941
71,592
71,291
84,035
66,110
68,491
69,733
68,642
67,432
72,219
72,184
73,201
64,362
78,095
64,248
85,113
65,478
77,703
85,401
100,859
88,314
58,755
62,961
83,911
102,254
79,436
66,610
73,435
90,766
70,729
69,428
64,586
79,997
64,042
62,421
73,847
120,610
78,269
77,530
68,716
55,512
113,619
118,573
115,936
87,369
63,537
65,266
71,104
66,056
87,782
64,837
63,350
61,349
66,025
49,389
79,272
92,585
74,020
83,816
67,130
84,474
76,257
82,591
75,023
74,772
60,867
81,956
67,876
71,063
67,273
73,812
62,174
63,844
70,187
76,859
73,692
63,760
80,142
76,287
74,438
72,207
76,350
82,443
75,942
74,837
75,195
71,734
54,055
64,238
70,553
67,517
71,415
79,665
77,071
65,869
56,650
72,962
61,742
54,170
68,754
70,780
73,926
62,606
52,777
60,428
64,856
76,013
74,298
65,484
77,048
66,770
71,369
66,050
66,018
63,535
74,143
82,538
72,110
65,905
58,056
67,830
71,817
63,785
71,941
75,169
64,738
68,052
64,954
69,390
80,782
66,472
89,907
84,019
74,995
71,304
68,655
73,709
83,141
84,197
88,133
80,245
89,017
66,463
68,601
80,106
58,473
85,251
85,017
69,326
77,145
67,011
82,745
101,709
69,985
89,887
100,341
91,392
71,818
88,015
63,848
66,279
74,699
66,810
73,348
73,347
50,422
78,166
54,903
61,035
82,237
63,174
55,058
70,886
58,787
57,439
67,073
93,709
36,562
69,517
67,726
63,690
88,724
86,387
67,922
79,775
74,626
93,747
76,479
65,049
67,299
85,943
80,845
67,975
73,543
89,106
67,457
60,484
71,655
70,529
85,055
75,903
72,431
83,464
72,768
71,280
85,517
76,457
72,101
64,438
80,183
70,186
64,816
72,375
75,826
62,658
73,303
84,901
64,990
86,385
76,271
68,320
83,409
75,262
55,246
86,129
82,539
45,610
59,251
69,701
76,995
67,096
62,569
49,861
67,458
69,017
61,348
59,579
61,506
63,825
66,934
70,183
53,646
77,102
56,203
73,533
69,839
75,650
76,629
63,800
54,810
76,290
61,138
62,909
62,578
65,292
70,840
59,313
65,687
58,408
75,073
60,146
65,416
72,720
88,930
77,363
53,166
59,886
70,731
92,774
87,209
66,317
75,043
72,106
60,380
76,133
61,894
57,180
73,655
98,990
67,747
67,705
87,595
69,219
95,983
104,463
133,606
72,776
55,903
79,633
83,507
66,103
92,631
72,278
71,641
62,728
69,953
62,930
88,985
95,688
75,593
88,928
70,509
88,261
84,652
95,933
77,406
78,318
63,079
95,498
79,569
55,766
71,952
56,073
81,295
76,213
70,450
83,417
81,443
75,454
80,175
84,598
72,038
66,042
85,362
80,725
82,620
73,128
76,840
78,313
74,209
72,257
78,439
76,870
76,788
78,721
73,679
83,634
73,602
83,823
81,522
80,637
65,664
79,164
67,189
62,531
64,786
68,931
77,706
73,640
67,140
79,589
75,635
74,416
84,088
68,325
77,350
76,063
70,993
68,128
78,101
79,550
70,054
68,489
73,726
70,714
63,199
72,635
67,668
68,066
62,042
61,592
66,371
60,522
86,820
79,694
74,781
68,476
70,221
58,019
82,578
82,194
78,203
73,021
82,514
67,607
66,894
80,537
54,529
92,703
76,611
63,788
58,614
68,355
71,913
86,466
67,460
81,556
86,464
76,859
79,726
77,445
72,425
80,104
66,063
83,606
49,135
52,282
56,187
51,619
54,131
52,203
44,547
69,276
71,250
57,636
77,783
62,783
58,364
63,277
56,516
57,426
56,836
82,032
31,862
64,273
76,056
67,189
59,098
69,331
64,672
55,576
59,028
54,600
60,215
73,382
76,399
53,296
64,653
76,740
64,052
52,043
63,290
65,677
74,994
69,626
64,714
58,831
79,166
67,132
61,515
63,947
67,491
56,789
58,246
56,707
73,918
59,231
82,694
47,079
61,913
49,077
37,484
56,141
34,299
49,479
50,216
39,005
45,797
41,701
59,837
48,636
57,232
43,913
40,929
52,670
84,622
101,908
62,877
60,696
78,337
61,317
57,645
63,979
50,216
58,380
43,272
43,808
73,635
58,293
56,954
58,759
51,674
63,150
46,650
41,198
61,880
65,633
64,928
101,944
88,205
54,248
75,516
95,272
71,298
78,913
79,163
80,363
76,382
76,206
74,224
60,022
75,810
91,045
70,798
75,203
63,124
74,761
79,625
81,408
71,533
85,831
57,656
96,129
75,842
85,104
106,308
83,555
77,581
87,569
71,555
76,033
78,575
69,096
83,562
78,062
74,632
69,379
91,764
74,894
82,583
87,754
106,998
95,859
66,405
74,780
95,560
119,410
96,268
83,597
94,361
120,233
84,264
89,177
83,614
90,443
76,762
74,262
88,729
129,458
87,007
83,321
91,618
66,222
120,334
112,276
99,534
89,040
66,106
76,205
93,653
78,231
96,219
85,527
94,105
83,781
60,021
70,013
90,090
123,091
88,067
91,567
81,982
102,180
84,749
103,877
78,770
80,368
65,894
101,278
89,725
82,743
79,039
88,339
82,062
76,860
76,409
79,442
84,985
67,739
95,874
86,653
79,816
83,342
89,529
92,121
88,532
86,743
75,935
92,814
73,915
84,846
93,947
89,361
78,112
71,596
89,574
88,123
72,879
128,781
101,484
75,041
83,122
83,754
105,284
102,152
78,215
82,671
81,475
100,263
81,526
75,209
90,204
78,674
81,556
84,193
78,328
70,836
85,133
84,123
76,250
69,825
77,316
81,202
84,641
75,891
49,341,554
99.24%
merged
53,107
84,095
78,102
42,312
56,350
60,026
69,362
68,792
60,989
67,566
75,264
63,761
56,472
42,785
63,898
56,920
56,831
50,613
60,157
64,402
62,794
68,012
54,097
63,683
50,743
82,873
68,331
68,109
80,219
63,250
65,511
67,062
65,653
65,111
69,668
69,633
70,181
61,798
74,650
61,429
81,813
62,576
75,092
82,582
97,817
85,489
56,758
60,545
80,429
98,182
76,111
63,752
69,983
86,813
68,749
67,007
62,497
77,757
62,144
60,529
71,071
116,379
75,124
74,334
65,838
53,182
110,223
115,405
112,656
84,739
61,464
63,125
67,918
62,947
83,861
61,883
60,079
58,566
63,033
47,049
75,326
88,074
70,021
79,826
63,933
81,066
72,874
78,885
71,915
71,764
58,187
78,817
65,170
68,021
64,611
70,750
59,322
60,940
67,076
73,304
70,238
61,168
76,814
73,078
71,111
69,068
72,999
78,884
72,753
71,852
71,893
68,535
51,454
60,822
67,213
64,567
68,527
76,146
73,727
63,153
53,659
69,281
58,446
51,357
65,476
67,040
70,508
59,603
50,203
57,453
62,083
72,305
70,823
62,877
74,402
63,941
67,691
63,011
62,773
60,165
70,636
78,788
68,945
62,952
55,043
64,771
68,199
60,817
69,027
71,981
61,718
65,316
62,423
66,298
77,548
64,273
86,248
80,799
72,461
68,364
67,330
71,692
81,139
82,987
86,139
78,509
87,323
64,950
66,738
77,933
56,836
82,981
82,953
67,270
74,902
64,691
79,581
98,387
68,961
87,320
97,484
87,521
69,246
85,460
62,176
64,363
73,172
65,463
71,908
72,076
49,393
76,385
52,763
58,212
78,844
61,010
52,746
68,472
56,328
55,337
65,514
87,254
35,516
67,807
65,828
61,297
87,168
83,747
66,277
76,774
72,532
90,761
74,964
63,584
65,551
83,442
78,599
66,087
71,730
86,613
65,482
58,897
69,740
69,441
82,628
73,224
70,082
81,465
70,341
69,686
83,888
74,705
69,055
61,526
76,760
66,978
62,090
68,978
72,591
59,744
70,624
82,009
62,371
82,915
73,708
65,506
79,967
72,310
52,847
82,725
79,425
43,390
56,862
66,615
73,800
64,371
59,991
47,681
64,524
66,184
58,965
57,227
58,742
61,219
64,050
67,369
51,325
73,661
53,475
70,553
67,023
72,630
73,618
60,908
52,347
73,122
58,322
60,232
59,833
62,217
67,821
56,432
62,564
55,870
71,413
57,310
62,286
69,214
85,951
74,644
50,982
57,642
67,903
89,386
83,836
63,605
71,568
68,731
57,618
72,566
58,996
54,361
70,919
95,469
65,105
65,072
84,206
65,930
92,114
100,841
129,645
70,187
54,014
76,948
80,723
63,924
90,059
69,711
69,939
61,517
68,385
61,460
87,224
93,167
73,747
87,022
68,629
86,109
82,800
92,997
75,415
76,137
61,476
93,205
77,173
54,483
70,295
54,802
79,349
74,739
68,746
81,267
79,848
73,708
78,088
83,041
69,661
64,429
82,771
78,711
80,056
70,401
74,520
76,086
71,719
70,019
75,635
73,582
75,266
76,943
71,899
81,737
71,841
81,752
79,419
78,381
64,539
77,585
65,697
60,693
63,097
67,382
75,197
70,709
66,035
77,884
74,271
72,749
82,268
66,808
75,008
73,465
69,223
66,465
76,413
78,032
68,117
66,944
71,429
68,956
61,111
70,079
65,408
66,340
59,468
59,247
63,259
57,870
85,229
78,213
73,336
67,252
68,727
56,865
80,411
79,931
76,105
71,209
80,115
65,782
65,056
78,352
53,074
90,059
74,645
62,254
56,964
66,562
69,761
83,957
65,447
79,025
84,373
74,655
77,458
74,964
71,338
78,754
64,889
82,270
46,917
49,623
53,507
48,964
51,353
49,822
41,981
66,032
69,118
55,987
75,866
61,218
56,016
59,862
54,178
53,678
55,216
79,626
31,033
62,736
73,388
63,899
56,454
64,615
62,890
54,075
57,747
53,519
58,030
69,620
73,620
50,231
62,777
74,774
62,441
50,515
60,130
61,296
72,239
64,959
63,210
57,568
77,463
65,632
59,655
61,857
64,745
54,786
57,143
55,744
72,641
58,185
80,991
46,109
60,650
48,038
36,780
55,116
33,665
48,606
49,191
38,320
45,030
40,852
58,416
47,204
56,130
42,830
40,225
51,568
82,590
99,717
61,285
59,002
76,878
60,190
56,639
62,771
49,413
57,078
41,270
41,980
70,770
55,725
54,555
56,459
49,379
60,241
45,651
40,253
60,640
64,349
63,136
97,748
85,049
50,956
74,410
93,484
70,032
77,691
77,157
76,480
73,180
71,756
72,768
58,838
74,464
89,527
69,024
72,080
61,296
70,668
78,110
79,899
70,537
84,170
55,213
90,516
73,755
79,912
102,031
79,953
74,416
84,058
68,739
73,044
75,503
66,240
81,594
75,904
72,282
67,217
89,246
73,032
80,813
85,409
104,451
93,093
64,434
72,688
92,955
116,325
93,836
81,448
91,248
116,842
81,738
86,541
81,135
87,832
75,710
71,752
87,323
127,205
85,268
81,555
89,675
64,723
118,226
110,429
95,676
85,507
63,356
73,165
90,985
76,091
93,848
82,505
91,555
81,469
58,572
67,673
88,129
119,208
85,197
88,920
79,033
98,188
82,089
100,565
76,502
78,070
63,464
97,981
86,871
80,143
76,449
85,645
80,193
75,244
74,747
77,711
82,799
66,007
94,429
84,946
78,000
81,575
87,610
90,307
86,211
84,586
74,548
91,053
72,356
83,114
91,858
87,682
76,728
70,459
88,351
86,320
70,142
125,137
99,375
72,212
81,922
81,319
103,305
99,662
74,755
80,030
78,974
97,410
79,472
73,607
88,048
76,661
79,809
82,312
76,529
69,213
83,482
81,941
74,422
68,214
75,670
78,922
82,699
73,976
47,683,448
95.91%
nonchim
47,965
74,073
70,336
38,650
51,103
53,557
61,688
61,776
54,477
58,783
66,921
57,147
51,299
39,546
57,280
51,454
51,386
45,352
53,702
57,316
54,061
60,431
47,445
54,355
39,607
64,886
55,429
53,140
62,741
51,254
53,568
53,904
53,321
51,696
55,200
56,051
59,547
51,974
60,922
52,385
68,436
51,643
62,457
66,876
82,279
72,205
47,645
48,260
64,554
79,536
61,436
51,978
56,699
67,957
52,134
53,733
47,912
59,046
46,915
46,088
60,002
99,621
64,233
61,527
55,376
43,764
89,101
95,116
94,430
71,417
49,385
51,193
53,409
49,162
68,746
48,783
47,477
46,345
50,328
37,915
62,712
74,043
58,241
65,650
54,571
68,019
60,894
63,731
58,787
59,009
47,221
61,094
50,435
55,394
52,728
56,652
48,969
49,722
55,996
59,396
58,161
50,857
63,211
58,486
61,001
55,736
61,701
64,057
58,452
58,893
56,973
56,655
40,511
48,687
54,074
52,098
54,718
60,533
58,615
51,105
44,208
56,758
49,619
42,027
52,782
53,004
56,968
50,310
41,112
45,719
50,744
57,600
56,046
50,404
60,375
51,974
56,966
52,571
51,636
50,117
56,000
63,453
57,436
51,378
43,644
53,778
56,710
47,071
54,372
56,136
47,899
52,389
50,870
53,205
61,007
52,217
66,250
62,381
58,596
54,401
61,356
60,538
68,813
72,271
75,188
67,401
74,751
55,893
61,550
67,518
51,803
67,387
71,013
61,535
63,516
55,687
71,356
83,889
55,609
80,334
88,134
73,595
61,604
76,593
54,561
49,868
58,955
54,574
61,391
61,591
42,550
60,977
41,395
46,000
63,095
48,253
41,322
55,275
43,432
42,912
56,568
77,058
30,611
58,990
59,513
56,100
79,509
77,299
58,477
67,017
65,607
82,268
68,919
55,296
57,794
76,185
65,844
59,066
62,436
78,299
55,325
52,654
58,458
63,707
75,169
65,144
62,185
74,231
61,076
56,628
68,056
70,559
56,268
49,799
61,731
54,329
49,184
53,876
57,725
46,626
58,813
68,053
53,133
69,785
59,951
52,631
62,247
57,084
41,515
64,966
62,773
36,007
43,976
52,627
60,053
52,599
49,226
38,207
51,506
52,869
46,486
46,692
47,707
50,142
52,019
56,766
43,052
58,528
42,562
58,069
52,902
57,359
57,005
49,104
42,412
59,232
45,258
48,632
48,787
48,405
54,630
45,922
51,218
45,712
59,396
47,016
49,275
53,580
70,218
58,567
42,370
47,057
54,094
71,805
68,072
51,774
59,660
54,079
48,130
58,871
49,036
42,351
56,005
80,298
51,958
54,498
67,255
54,003
76,704
85,230
102,626
55,268
43,371
60,760
63,992
49,679
73,430
55,710
59,217
53,345
56,973
52,061
75,270
80,123
62,080
68,637
60,352
72,897
69,769
79,108
61,711
63,381
50,607
70,245
65,962
46,698
59,390
46,242
68,126
62,536
56,510
68,332
68,544
61,369
64,075
73,105
55,688
52,725
65,095
64,474
63,774
55,360
60,902
61,321
57,791
56,600
62,314
58,751
69,325
67,923
58,949
71,945
54,067
65,536
62,851
61,684
60,084
70,540
54,554
51,047
54,044
56,946
65,084
61,906
51,709
66,242
69,192
62,465
69,702
56,937
62,213
60,467
54,344
56,521
63,492
69,422
58,540
57,462
59,493
62,402
47,288
59,995
52,756
58,216
49,435
48,007
49,578
45,717
77,826
71,306
66,902
61,576
59,156
50,913
66,765
66,638
69,732
65,276
72,673
60,500
54,296
72,080
48,958
79,626
66,540
55,535
50,478
59,412
61,071
73,949
54,734
68,212
76,322
68,408
70,264
68,134
70,766
77,706
64,228
81,008
37,899
39,672
42,993
39,700
41,757
39,691
33,951
53,921
56,578
44,718
58,509
53,881
47,059
45,613
44,070
41,134
50,515
68,287
27,614
56,707
62,592
53,367
45,855
50,493
51,208
42,033
48,061
48,177
49,449
52,736
62,479
38,177
51,679
60,210
56,111
39,811
50,035
48,729
56,817
51,200
51,769
52,925
70,478
60,498
52,877
49,197
49,981
44,581
51,466
50,484
65,198
52,805
66,940
40,410
47,756
36,947
33,492
50,353
30,681
44,260
37,425
35,282
41,060
35,550
49,937
39,775
52,237
40,109
37,409
46,990
68,353
90,838
58,615
50,637
70,848
55,159
52,808
60,712
45,770
54,480
34,194
34,785
55,647
46,164
45,892
45,028
41,314
50,597
35,036
31,116
45,111
54,442
52,155
76,078
69,464
39,515
70,863
79,434
63,604
70,932
67,357
61,586
59,604
57,543
60,019
47,857
62,941
82,759
60,720
57,938
51,337
56,675
66,706
66,384
65,889
67,611
46,329
70,859
60,067
64,313
87,880
68,582
63,595
72,869
57,836
61,498
62,936
55,986
67,662
63,199
58,651
57,380
76,194
64,061
74,302
77,528
90,887
77,687
55,543
63,094
80,104
104,854
83,174
75,752
79,553
100,347
70,366
70,777
68,527
74,214
75,304
62,139
85,874
123,982
82,622
78,297
86,612
62,036
114,855
107,963
81,324
68,608
50,717
60,087
84,687
62,793
83,166
72,407
84,859
71,876
51,856
60,133
79,023
109,985
75,238
77,836
70,960
88,780
73,968
89,700
65,873
66,441
53,654
84,445
71,280
65,944
63,224
71,841
66,490
59,305
58,002
60,807
66,637
53,992
85,042
74,684
66,289
64,963
72,687
71,728
68,311
71,245
64,538
79,365
57,610
73,317
81,053
69,996
67,549
61,049
88,351
77,106
57,094
117,143
93,672
67,167
78,345
74,882
100,970
95,344
61,903
64,862
66,193
82,187
69,787
59,284
73,491
63,563
63,448
64,522
64,915
58,438
69,614
70,359
62,013
58,524
61,136
68,190
70,630
63,356
40,264,149
80.98%
This table can be downloaded as an Excel table below:
5. DADA2 Amplicon Sequence Variants (ASVs). A total of 9960 unique merged and chimera-free ASV sequences were identified, and their corresponding
read counts for each sample are available in the "ASV Read Count Table" with rows for the ASV sequences and columns for sample. This read count table can be used for
microbial profile comparison among different samples and the sequences provided in the table can be used to taxonomy assignment.
The species-level, open-reference 16S rRNA NGS reads taxonomy assignment pipeline
Version 20210310a
The close-reference taxonomy assignment of the ASV sequences using BLASTN is based on the algorithm published by Al-Hebshi et. al. (2015)[2].
1. Raw sequences reads in FASTA format were BLASTN-searched against a combined set of 16S rRNA reference sequences - the FOMC 16S rRNA Reference Sequences version 20221029 (https://microbiome.forsyth.org/ftp/refseq/).
This set consists of the HOMD (version 15.22 http://www.homd.org/index.php?name=seqDownload&file&type=R ), Mouse Oral Microbiome Database (MOMD version 5.1 https://momd.org/ftp/16S_rRNA_refseq/MOMD_16S_rRNA_RefSeq/V5.1/),
and the NCBI 16S rRNA reference sequence set (https://ftp.ncbi.nlm.nih.gov/blast/db/16S_ribosomal_RNA.tar.gz).
These sequences were screened and combined to remove short sequences (<1000nt), chimera, duplicated and sub-sequences,
as well as sequences with poor taxonomy annotation (e.g., without species information).
This process resulted in 1,015 full-length 16S rRNA sequences from HOMD V15.22, 356 from MOMD V5.1, and 22,126 from NCBI, a total of 23,497 sequences.
Altogether these sequence represent a total of 17,035 oral and non-oral microbial species.
The NCBI BLASTN version 2.7.1+ (Zhang et al, 2000) [3] was used with the default parameters.
Reads with ≥ 98% sequence identity to the matched reference and ≥ 90% alignment length
(i.e., ≥ 90% of the read length that was aligned to the reference and was used to calculate
the sequence percent identity) were classified based on the taxonomy of the reference sequence
with highest sequence identity. If a read matched with reference sequences representing
more than one species with equal percent identity and alignment length, it was subject
to chimera checking with USEARCH program version v8.1.1861 (Edgar 2010). Non-chimeric reads with multi-species
best hits were considered valid and were assigned with a unique species
notation (e.g., spp) denoting unresolvable multiple species.
2. Unassigned reads (i.e., reads with < 98% identity or < 90% alignment length) were pooled together and reads < 200 bases were
removed. The remaining reads were subject to the de novo
operational taxonomy unit (OTU) calling and chimera checking using the USEARCH program version v8.1.1861 (Edgar 2010)[4].
The de novo OTU calling and chimera checking was done using 98% as the sequence identity cutoff, i.e., the species-level OTU.
The output of this step produced species-level de novo clustered OTUs with 98% identity.
Representative reads from each of the OTUs/species were then BLASTN-searched
against the same reference sequence set again to determine the closest species for
these potential novel species. These potential novel species were pooled together with the reads that were signed to specie-level in
the previous step, for down-stream analyses.
Reference:
Al-Hebshi NN, Nasher AT, Idris AM, Chen T. Robust species taxonomy assignment algorithm for 16S rRNA NGS reads: application
to oral carcinoma samples. J Oral Microbiol. 2015 Sep 29;7:28934. doi: 10.3402/jom.v7.28934. PMID: 26426306; PMCID: PMC4590409.
Zhang Z, Schwartz S, Wagner L, Miller W. A greedy algorithm for aligning DNA sequences. J Comput Biol. 2000 Feb-Apr;7(1-2):203-14. doi: 10.1089/10665270050081478. PMID: 10890397.
Edgar RC. Search and clustering orders of magnitude faster than BLAST.
Bioinformatics. 2010 Oct 1;26(19):2460-1. doi: 10.1093/bioinformatics/btq461. Epub 2010 Aug 12. PubMed PMID: 20709691.
3. Designations used in the taxonomy:
1) Taxonomy levels are indicated by these prefixes:
k__: domain/kingdom
p__: phylum
c__: class
o__: order
f__: family
g__: genus
s__: species
Example:
k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Blautia;s__faecis
2) Unique level identified – known species:
k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Roseburia;s__hominis
The above example shows some reads match to a single species (all levels are unique)
3) Non-unique level identified – known species:
k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Roseburia;s__multispecies_spp123_3
The above example “s__multispecies_spp123_3” indicates certain reads equally match to 3 species of the
genus Roseburia; the “spp123” is a temporally assigned species ID.
k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__multigenus;s__multispecies_spp234_5
The above example indicates certain reads match equally to 5 different species, which belong to multiple genera.;
the “spp234” is a temporally assigned species ID.
4) Unique level identified – unknown species, potential novel species:
k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Roseburia;s__ hominis_nov_97%
The above example indicates that some reads have no match to any of the reference sequences with
sequence identity ≥ 98% and percent coverage (alignment length) ≥ 98% as well. However this groups
of reads (actually the representative read from a de novo OTU) has 96% percent identity to
Roseburia hominis, thus this is a potential novel species, closest to Roseburia hominis.
(But they are not the same species).
5) Multiple level identified – unknown species, potential novel species:
k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Roseburia;s__ multispecies_sppn123_3_nov_96%
The above example indicates that some reads have no match to any of the reference sequences
with sequence identity ≥ 98% and percent coverage (alignment length) ≥ 98% as well.
However this groups of reads (actually the representative read from a de novo OTU)
has 96% percent identity equally to 3 species in Roseburia. Thus this is no single
closest species, instead this group of reads match equally to multiple species at 96%.
Since they have passed chimera check so they represent a novel species. “sppn123” is a
temporary ID for this potential novel species.
4. The taxonomy assignment algorithm is illustrated in this flow char below:
Read Taxonomy Assignment - Result Summary *
Code
Category
MPC=0% (>=1 read)
MPC=0.01%(>=4021 reads)
A
Total reads
40,264,149
40,264,149
B
Total assigned reads
40,218,977
40,218,977
C
Assigned reads in species with read count < MPC
0
283,287
D
Assigned reads in samples with read count < 500
0
0
E
Total samples
670
670
F
Samples with reads >= 500
670
670
G
Samples with reads < 500
0
0
H
Total assigned reads used for analysis (B-C-D)
40,218,977
39,935,690
I
Reads assigned to single species
35,763,459
35,546,808
J
Reads assigned to multiple species
4,004,554
3,982,901
K
Reads assigned to novel species
450,964
405,981
L
Total number of species
1,153
146
M
Number of single species
615
122
N
Number of multi-species
53
12
O
Number of novel species
485
12
P
Total unassigned reads
45,172
45,172
Q
Chimeric reads
634
634
R
Reads without BLASTN hits
23,158
23,158
S
Others: short, low quality, singletons, etc.
21,380
21,380
A=B+P=C+D+H+Q+R+S
E=F+G
B=C+D+H
H=I+J+K
L=M+N+O
P=Q+R+S
* MPC = Minimal percent (of all assigned reads) read count per species, species with read count < MPC were removed.
* Samples with reads < 500 were removed from downstream analyses.
* The assignment result from MPC=0.1% was used in the downstream analyses.
Read Taxonomy Assignment - ASV Species-Level Read Counts Table
This table shows the read counts for each sample (columns) and each species identified based on the ASV sequences.
The downstream analyses were based on this table.
The species listed in the table has full taxonomy and a dynamically assigned species ID specific to this report.
When some reads match with the reference sequences of more than one species equally (i.e., same percent identiy and alignmnet coverage),
they can't be assigned to a particular species. Instead, they are assigned to multiple species with the species notaton
"s__multispecies_spp2_2". In this notation, spp2 is the dynamic ID assigned to these reads that hit multiple sequences and the "_2"
at the end of the notation means there are two species in the spp2.
You can look up which species are included in the multi-species assignment, in this table below:
Another type of notation is "s__multispecies_sppn2_2", in which the "n" in the sppn2 means it's a potential novel species because all the reads in this species
have < 98% idenity to any of the reference sequences. They were grouped together based on de novo OTU clustering at 98% identity cutoff. And then
a representative sequence was chosed to BLASTN search against the reference database to find the closest match (but will still be < 98%). This representative
sequence also matched equally to more than one species, hence the "spp" was given in the label.
SST A Final PMA+ vs SST B Final PMA+ vs SST C Final PMA+ vs SST D Final PMA+ vs SST E Final PMA+ vs SST F Final PMA+ vs SST G Final PMA+ vs SST H Final PMA+ vs SST I Final PMA+ vs SST J Final PMA+
SST A Final PMA- vs SST B Final PMA- vs SST C Final PMA- vs SST D Final PMA- vs SST E Final PMA- vs SST F Final PMA- vs SST G Final PMA- vs SST H Final PMA- vs SST I Final PMA- vs SST J Final PMA-
SMT A Final PMA+ vs SMT B Final PMA+ vs SMT C Final PMA+ vs SMT D Final PMA+ vs SMT E Final PMA+ vs SMT F Final PMA+ vs SMT G Final PMA+ vs SMT H Final PMA+ vs SMT I Final PMA+ vs SMT J Final PMA+
SMT A Final PMA- vs SMT B Final PMA- vs SMT C Final PMA- vs SMT D Final PMA- vs SMT E Final PMA- vs SMT F Final PMA- vs SMT G Final PMA- vs SMT H Final PMA- vs SMT I Final PMA- vs SMT J Final PMA-
In ecology, alpha diversity (α-diversity) is the mean species diversity in sites or habitats at a local scale.
The term was introduced by R. H. Whittaker[5][6] together with the terms beta diversity (β-diversity)
and gamma diversity (γ-diversity). Whittaker's idea was that the total species diversity in a landscape
(gamma diversity) is determined by two different things, the mean species diversity in sites or habitats
at a more local scale (alpha diversity) and the differentiation among those habitats (beta diversity).
Diversity measures are affected by the sampling depth. Rarefaction is a technique to assess species richness from the results of sampling. Rarefaction allows
the calculation of species richness for a given number of individual samples, based on the construction
of so-called rarefaction curves. This curve is a plot of the number of species as a function of the
number of samples. Rarefaction curves generally grow rapidly at first, as the most common species are found,
but the curves plateau as only the rarest species remain to be sampled [7].
The two main factors taken into account when measuring diversity are richness and evenness.
Richness is a measure of the number of different kinds of organisms present in a particular area.
Evenness compares the similarity of the population size of each of the species present. There are
many different ways to measure the richness and evenness. These measurements are called "estimators" or "indices".
Below is a diversity of 3 commonly used indices showing the values for all the samples (dots) and in groups (boxes) at the species level.
Printed on each graph is the statistical significance p values of the difference between the groups.
The significance is calculated using either Kruskal-Wallis test or the Wilcoxon rank sum test, both are non-parametric methods (since
microbiome read count data are considered non-normally distributed) for testing
whether samples originate from the same distribution (i.e., no difference between groups). The Kruskal-Wallis test is used to compare three or more
independent groups to determine if there are statistically significant differences between their medians. The Wilcoxon Rank Sum test, also known as
the Mann-Whitney U test, is used to compare two independent groups to determine if there is a significant difference between their distributions.
The p-value is shown on the top of each graph. A p-value < 0.05 is considered statistically significant between/among the test groups.
 
Alpha Diversity Box Plots for All Groups - Species Level
 
 
 
Alpha Diversity Box Plots for Individual Comparisons at Species level
SST A Final PMA+ vs SST B Final PMA+ vs SST C Final PMA+ vs SST D Final PMA+ vs SST E Final PMA+ vs SST F Final PMA+ vs SST G Final PMA+ vs SST H Final PMA+ vs SST I Final PMA+ vs SST J Final PMA+
SST A Final PMA- vs SST B Final PMA- vs SST C Final PMA- vs SST D Final PMA- vs SST E Final PMA- vs SST F Final PMA- vs SST G Final PMA- vs SST H Final PMA- vs SST I Final PMA- vs SST J Final PMA-
SMT A Final PMA+ vs SMT B Final PMA+ vs SMT C Final PMA+ vs SMT D Final PMA+ vs SMT E Final PMA+ vs SMT F Final PMA+ vs SMT G Final PMA+ vs SMT H Final PMA+ vs SMT I Final PMA+ vs SMT J Final PMA+
SMT A Final PMA- vs SMT B Final PMA- vs SMT C Final PMA- vs SMT D Final PMA- vs SMT E Final PMA- vs SMT F Final PMA- vs SMT G Final PMA- vs SMT H Final PMA- vs SMT I Final PMA- vs SMT J Final PMA-
Beta diversity compares the similarity (or dissimilarity) of microbial profiles between different
groups of samples. There are many different similarity/dissimilarity metrics [8].
In general, they can be quantitative (using sequence abundance, e.g., Bray-Curtis or weighted UniFrac)
or binary (considering only presence-absence of sequences, e.g., binary Jaccard or unweighted UniFrac).
They can be even based on phylogeny (e.g., UniFrac metrics) or not (non-UniFrac metrics, such as Bray-Curtis, etc.).
For microbiome studies, species profiles of samples can be compared with the Bray-Curtis dissimilarity,
which is based on the count data type. The pair-wise Bray-Curtis dissimilarity matrix of all samples can then be
subject to either multi-dimensional scaling (MDS, also known as PCoA) or non-metric MDS (NMDS).
MDS/PCoA is a
scaling or ordination method that starts with a matrix of similarities or dissimilarities
between a set of samples and aims to produce a low-dimensional graphical plot of the data
in such a way that distances between points in the plot are close to original dissimilarities.
NMDS is similar to MDS, however it does not use the dissimilarities data, instead it converts them into
the ranks and use these ranks in the calculation.
In our beta diversity analysis, Bray-Curtis dissimilarity matrix was first calculated and then plotted by the PCoA and
NMDS separately. Below are beta diveristy results for all groups together, at the Species level:
 
 
NMDS and PCoA Plots for All Groups - Species Level
 
 
 
 
 
The above PCoA and NMDS plots are based on count data. The count data can also be transformed into centered log ratio (CLR)
for each species. The CLR data is no longer count data and cannot be used in Bray-Curtis dissimilarity calculation. Instead
CLR can be compared with Euclidean distances. When CLR data are compared by Euclidean distance, the distance is also called
Aitchison distance.
Below are the NMDS and PCoA plots of the Aitchison distances of the samples at the Species level:
 
 
 
 
 
NMDS and PCoA Plots for Individual Comparisons at Species level
SST A Final PMA+ vs SST B Final PMA+ vs SST C Final PMA+ vs SST D Final PMA+ vs SST E Final PMA+ vs SST F Final PMA+ vs SST G Final PMA+ vs SST H Final PMA+ vs SST I Final PMA+ vs SST J Final PMA+
SST A Final PMA- vs SST B Final PMA- vs SST C Final PMA- vs SST D Final PMA- vs SST E Final PMA- vs SST F Final PMA- vs SST G Final PMA- vs SST H Final PMA- vs SST I Final PMA- vs SST J Final PMA-
SMT A Final PMA+ vs SMT B Final PMA+ vs SMT C Final PMA+ vs SMT D Final PMA+ vs SMT E Final PMA+ vs SMT F Final PMA+ vs SMT G Final PMA+ vs SMT H Final PMA+ vs SMT I Final PMA+ vs SMT J Final PMA+
SMT A Final PMA- vs SMT B Final PMA- vs SMT C Final PMA- vs SMT D Final PMA- vs SMT E Final PMA- vs SMT F Final PMA- vs SMT G Final PMA- vs SMT H Final PMA- vs SMT I Final PMA- vs SMT J Final PMA-
16S rRNA next generation sequencing (NGS) generates a fixed number of reads that reflect the proportion of different
species in a sample, i.e., the relative abundance of species, instead of the absolute abundance.
In Mathematics, measurements involving probabilities, proportions, percentages, and ppm can all
be thought of as compositional data. This makes the microbiome read count data “compositional”
(Gloor et al, 2017). In general, compositional data represent parts of a whole which only
carry relative information [9].
The problem of microbiome data being compositional arises when comparing two groups of samples for
identifying “differentially abundant” species. A species with the same absolute abundance between two
conditions, its relative abundances in the two conditions (e.g., percent abundance) can become different
if the relative abundance of other species change greatly. This problem can lead to incorrect conclusion
in terms of differential abundance for microbial species in the samples.
When studying differential abundance (DA), the current better approach is to transform the read count
data into log ratio data. The ratios are calculated between read counts of all species in a sample to
a “reference” count (e.g., mean read count of the sample). The log ratio data allow the detection of DA
species without being affected by percentage bias mentioned above
In this report, a compositional DA analysis tool “ANCOM” (analysis of composition of microbiomes)
was used [10]. ANCOM transforms the count data into log-ratios and thus is more suitable for comparing
the composition of microbiomes in two or more populations. "ANCOM" generates a table of features with
W-statistics and whether the null hypothesis is rejected. The “W” is the W-statistic, or number of
features that a single feature is tested to be significantly different against. Hence the higher the "W"
the more statistical sifgnificant that a feature/species is differentially abundant.
Starting with version V1.2, we include the results of ANCOM-BC (Analysis of Compositions of
Microbiomes with Bias Correction) (Lin and Peddada 2020) [11]. ANCOM-BC is an updated version of "ANCOM" that:
(a) provides statistically valid test with appropriate p-values,
(b) provides confidence intervals for differential abundance of each taxon,
(c) controls the False Discovery Rate (FDR),
(d) maintains adequate power, and
(e) is computationally simple to implement.
The bias correction (BC) addresses a challenging problem of the bias introduced by differences in
the sampling fractions across samples. This bias has been a major hurdle in performing DA analysis of microbiome data.
ANCOM-BC estimates the unknown sampling fractions and corrects the bias induced by their differences among samples.
The absolute abundance data are modeled using a linear regression framework.
Starting with version V1.43, ANCOM-BC2 is used instead of ANCOM-BC, So that multiple pairwise directional test can be performed (if there are more than two gorups in a comparison).
When performing pairwise directional test, the mixed directional false discover rate (mdFDR) is taken into account. The mdFDR
is the combination of false discovery rate due to multiple testing, multiple pairwise comparisons, and directional tests within
each pairwise comparison. The mdFDR is adopted from (Guo, Sarkar, and Peddada 2010 [12]; Grandhi, Guo, and Peddada 2016 [13]). For more detail
explanation and additional features of ANCOM-BC2 please see author's documentation.
References:
Gloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ. Microbiome Datasets Are Compositional: And This Is Not Optional. Front Microbiol.
2017 Nov 15;8:2224. doi: 10.3389/fmicb.2017.02224. PMID: 29187837; PMCID: PMC5695134.
Mandal S, Van Treuren W, White RA, Eggesbø M, Knight R, Peddada SD. Analysis of composition of
microbiomes: a novel method for studying microbial composition. Microb Ecol Health Dis.
2015 May 29;26:27663. doi: 10.3402/mehd.v26.27663. PMID: 26028277; PMCID: PMC4450248.
Lin H, Peddada SD. Analysis of compositions of microbiomes with bias correction.
Nat Commun. 2020 Jul 14;11(1):3514. doi: 10.1038/s41467-020-17041-7.
PMID: 32665548; PMCID: PMC7360769.
Guo W, Sarkar SK, Peddada SD. Controlling false discoveries in multidimensional directional decisions, with applications to gene expression data on ordered categories. Biometrics. 2010 Jun;66(2):485-92. doi: 10.1111/j.1541-0420.2009.01292.x. Epub 2009 Jul 23. PMID: 19645703; PMCID: PMC2895927.
Grandhi A, Guo W, Peddada SD. A multiple testing procedure for multi-dimensional pairwise comparisons with application to gene expression studies. BMC Bioinformatics. 2016 Feb 25;17:104. doi: 10.1186/s12859-016-0937-5. PMID: 26917217; PMCID: PMC4768411.
LEfSe (Linear Discriminant Analysis Effect Size) is an alternative method to find "organisms, genes, or
pathways that consistently explain the differences between two or more microbial communities" (Segata et al., 2011) [14].
Specifically, LEfSe uses rank-based Kruskal-Wallis (KW) sum-rank test to detect features with significant
differential (relative) abundance with respect to the class of interest. Since it is rank-based, instead of proportional based,
the differential species identified among the comparison groups is less biased (than percent abundance based).
Reference:
Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation. Genome Biol. 2011 Jun 24;12(6):R60. doi: 10.1186/gb-2011-12-6-r60. PMID: 21702898; PMCID: PMC3218848.
SST A Final PMA+ vs SST B Final PMA+ vs SST C Final PMA+ vs SST D Final PMA+ vs SST E Final PMA+ vs SST F Final PMA+ vs SST G Final PMA+ vs SST H Final PMA+ vs SST I Final PMA+ vs SST J Final PMA+
SST A Final PMA- vs SST B Final PMA- vs SST C Final PMA- vs SST D Final PMA- vs SST E Final PMA- vs SST F Final PMA- vs SST G Final PMA- vs SST H Final PMA- vs SST I Final PMA- vs SST J Final PMA-
SMT A Final PMA+ vs SMT B Final PMA+ vs SMT C Final PMA+ vs SMT D Final PMA+ vs SMT E Final PMA+ vs SMT F Final PMA+ vs SMT G Final PMA+ vs SMT H Final PMA+ vs SMT I Final PMA+ vs SMT J Final PMA+
SMT A Final PMA- vs SMT B Final PMA- vs SMT C Final PMA- vs SMT D Final PMA- vs SMT E Final PMA- vs SMT F Final PMA- vs SMT G Final PMA- vs SMT H Final PMA- vs SMT I Final PMA- vs SMT J Final PMA-
SST A Final PMA+ vs SST B Final PMA+ vs SST C Final PMA+ vs SST D Final PMA+ vs SST E Final PMA+ vs SST F Final PMA+ vs SST G Final PMA+ vs SST H Final PMA+ vs SST I Final PMA+ vs SST J Final PMA+
SST A Final PMA- vs SST B Final PMA- vs SST C Final PMA- vs SST D Final PMA- vs SST E Final PMA- vs SST F Final PMA- vs SST G Final PMA- vs SST H Final PMA- vs SST I Final PMA- vs SST J Final PMA-
SMT A Final PMA+ vs SMT B Final PMA+ vs SMT C Final PMA+ vs SMT D Final PMA+ vs SMT E Final PMA+ vs SMT F Final PMA+ vs SMT G Final PMA+ vs SMT H Final PMA+ vs SMT I Final PMA+ vs SMT J Final PMA+
SMT A Final PMA- vs SMT B Final PMA- vs SMT C Final PMA- vs SMT D Final PMA- vs SMT E Final PMA- vs SMT F Final PMA- vs SMT G Final PMA- vs SMT H Final PMA- vs SMT I Final PMA- vs SMT J Final PMA-
SST A Final PMA+ vs SST B Final PMA+ vs SST C Final PMA+ vs SST D Final PMA+ vs SST E Final PMA+ vs SST F Final PMA+ vs SST G Final PMA+ vs SST H Final PMA+ vs SST I Final PMA+ vs SST J Final PMA+
SST A Final PMA- vs SST B Final PMA- vs SST C Final PMA- vs SST D Final PMA- vs SST E Final PMA- vs SST F Final PMA- vs SST G Final PMA- vs SST H Final PMA- vs SST I Final PMA- vs SST J Final PMA-
SMT A Final PMA+ vs SMT B Final PMA+ vs SMT C Final PMA+ vs SMT D Final PMA+ vs SMT E Final PMA+ vs SMT F Final PMA+ vs SMT G Final PMA+ vs SMT H Final PMA+ vs SMT I Final PMA+ vs SMT J Final PMA+
SMT A Final PMA- vs SMT B Final PMA- vs SMT C Final PMA- vs SMT D Final PMA- vs SMT E Final PMA- vs SMT F Final PMA- vs SMT G Final PMA- vs SMT H Final PMA- vs SMT I Final PMA- vs SMT J Final PMA-
To analyze the co-occurrence or co-exclusion between microbial species among different samples, network correlation
analysis tools are usually used for this purpose. However, microbiome count data are compositional. If count data are normalized to the total number of counts in the
sample, the data become not independent and traditional statistical metrics (e.g., correlation) for the detection
of specie-species relationships can lead to spurious results. In addition, sequencing-based studies typically
measure hundreds of OTUs (species) on few samples; thus, inference of OTU-OTU association networks is severely
under-powered. We provide the network association result with SparCC (Sparse Correlations for Compositional data)(Friedman & Alm 2012), which
is a method for inferring correlations from compositional data. SparCC estimates the linear Pearson correlations between
the log-transformed components.
The results of this analysis are for research purpose only. They are not intended to diagnose, treat, cure, or prevent any disease. Forsyth and FOMC
are not responsible for use of information provided in this report outside the research area.