Table of Content
I.	Project Summary
II.	Workflow Checklist
III.	NGS Sequencing Results
IV.	Complete Report Download
V.	Raw Sequence Data Download
VI.	Analysis - DADA2 Read Processing
	Sample Meta Info
	Read Count by Sample
VII.	Analysis - Read Taxonomy Assignment
	Taxonomy Barplots
VIII.	Analysis - Alpha Diversity
IX.	Analysis - Beta Diversity
X.	Analysis - Differential Abundance
	ANCOM Result
	LEfSe Result
XI.	Analysis - Heatmap Profile
XII.	Analysis - Network Association
XIII.	Disclaimer

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FOMC Service Report

16S rRNA Gene V1V3 Amplicon Sequencing

Version V1.52

Version History

The Forsyth Institute, Cambridge, MA, USA

June 21, 2026

Project ID: 20260618_CLIFF

I. Project Summary

Project 20260618_CLIFF 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.

II. Workflow Checklist

☑	1.	Sample Received
☑	2.	Sample Quality Evaluated
☑	3.	Sample Prepared for Sequencing
☑	4.	Next-Gen Sequencing
☑	5.	Sequence Quality Check
☑	6.	Absolute Abundance
☑	7.	Report and Raw Sequence Data Available for Download
☑	8.	Bioinformatics Analysis - Reads Processing (DADA2 Quality Trimming, Denoising, Paired Reads Merging)
☑	9.	Bioinformatics Analysis - Reads Taxonomy Assignment
☑	10.	Bioinformatics Analysis - Alpha Diversity Analysis
☑	11.	Bioinformatics Analysis - Beta Diversity Analysis
☑	12.	Bioinformatics Analysis - Differential Abundance Analysis
☑	13.	Bioinformatics Analysis - Heatmap Profile
☑	14.	Bioinformatics Analysis - Network Association

III. NGS Sequencing

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:

Absolute Abundance Standard Curve

IV. Complete Report Download

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.

V. Raw Sequence Data Download

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
F73312.S01 fastq_ori/ERR12711800_1.fastq fastq_ori/ERR12711800_2.fastq
F73312.S02 fastq_ori/ERR12711803_1.fastq fastq_ori/ERR12711803_2.fastq
F73312.S03 fastq_ori/ERR12711807_1.fastq fastq_ori/ERR12711807_2.fastq
F73312.S04 fastq_ori/ERR12711813_1.fastq fastq_ori/ERR12711813_2.fastq
F73312.S05 fastq_ori/ERR12711900_1.fastq fastq_ori/ERR12711900_2.fastq
F73312.S06 fastq_ori/ERR12711905_1.fastq fastq_ori/ERR12711905_2.fastq
F73312.S07 fastq_ori/ERR12712136_1.fastq fastq_ori/ERR12712136_2.fastq
F73312.S08 fastq_ori/ERR12712138_1.fastq fastq_ori/ERR12712138_2.fastq
F73312.S09 fastq_ori/ERR12712141_1.fastq fastq_ori/ERR12712141_2.fastq
F73312.S10 fastq_ori/ERR12712145_1.fastq fastq_ori/ERR12712145_2.fastq
F73312.S11 fastq_ori/ERR12712151_1.fastq fastq_ori/ERR12712151_2.fastq
F73312.S12 fastq_ori/ERR12712157_1.fastq fastq_ori/ERR12712157_2.fastq
F73312.S13 fastq_ori/ERR12712160_1.fastq fastq_ori/ERR12712160_2.fastq
F73312.S14 fastq_ori/ERR12712164_1.fastq fastq_ori/ERR12712164_2.fastq
F73312.S15 fastq_ori/ERR12712167_1.fastq fastq_ori/ERR12712167_2.fastq
F73312.S16 fastq_ori/ERR12712183_1.fastq fastq_ori/ERR12712183_2.fastq
F73312.S17 fastq_ori/ERR12712184_1.fastq fastq_ori/ERR12712184_2.fastq
F73312.S18 fastq_ori/ERR12712190_1.fastq fastq_ori/ERR12712190_2.fastq
F73312.S19 fastq_ori/ERR12712191_1.fastq fastq_ori/ERR12712191_2.fastq
F73312.S20 fastq_ori/ERR12712192_1.fastq fastq_ori/ERR12712192_2.fastq
F73312.S21 fastq_ori/ERR12712193_1.fastq fastq_ori/ERR12712193_2.fastq
F73312.S22 fastq_ori/ERR12712194_1.fastq fastq_ori/ERR12712194_2.fastq
F73312.S23 fastq_ori/ERR12712195_1.fastq fastq_ori/ERR12712195_2.fastq
F73312.S24 fastq_ori/ERR12712196_1.fastq fastq_ori/ERR12712196_2.fastq
F73312.S25 fastq_ori/ERR12712197_1.fastq fastq_ori/ERR12712197_2.fastq
F73312.S26 fastq_ori/ERR12712198_1.fastq fastq_ori/ERR12712198_2.fastq
F73312.S27 fastq_ori/ERR12712199_1.fastq fastq_ori/ERR12712199_2.fastq
F73312.S28 fastq_ori/ERR12712200_1.fastq fastq_ori/ERR12712200_2.fastq
F73312.S29 fastq_ori/ERR12712201_1.fastq fastq_ori/ERR12712201_2.fastq
F73312.S30 fastq_ori/ERR12712202_1.fastq fastq_ori/ERR12712202_2.fastq
F73312.S31 fastq_ori/ERR12712203_1.fastq fastq_ori/ERR12712203_2.fastq
F73312.S32 fastq_ori/ERR12712204_1.fastq fastq_ori/ERR12712204_2.fastq
F73312.S33 fastq_ori/ERR12712205_1.fastq fastq_ori/ERR12712205_2.fastq
F73312.S34 fastq_ori/ERR12712206_1.fastq fastq_ori/ERR12712206_2.fastq
F73312.S35 fastq_ori/ERR12712207_1.fastq fastq_ori/ERR12712207_2.fastq
F73312.S36 fastq_ori/ERR12712208_1.fastq fastq_ori/ERR12712208_2.fastq
F73312.S37 fastq_ori/ERR12712209_1.fastq fastq_ori/ERR12712209_2.fastq
F73312.S38 fastq_ori/ERR12712210_1.fastq fastq_ori/ERR12712210_2.fastq
F73312.S39 fastq_ori/ERR12712211_1.fastq fastq_ori/ERR12712211_2.fastq
F73312.S40 fastq_ori/ERR12712212_1.fastq fastq_ori/ERR12712212_2.fastq
F73312.S41 fastq_ori/ERR12712213_1.fastq fastq_ori/ERR12712213_2.fastq
F73312.S42 fastq_ori/ERR12712214_1.fastq fastq_ori/ERR12712214_2.fastq
F73312.S43 fastq_ori/ERR12712215_1.fastq fastq_ori/ERR12712215_2.fastq
F73312.S44 fastq_ori/ERR12712216_1.fastq fastq_ori/ERR12712216_2.fastq
F73312.S45 fastq_ori/ERR12712217_1.fastq fastq_ori/ERR12712217_2.fastq
F73312.S46 fastq_ori/ERR12712218_1.fastq fastq_ori/ERR12712218_2.fastq
F73312.S47 fastq_ori/ERR12712219_1.fastq fastq_ori/ERR12712219_2.fastq
F73312.S48 fastq_ori/ERR12712220_1.fastq fastq_ori/ERR12712220_2.fastq
F73312.S49 fastq_ori/ERR12712221_1.fastq fastq_ori/ERR12712221_2.fastq
F73312.S50 fastq_ori/ERR12712222_1.fastq fastq_ori/ERR12712222_2.fastq
F73312.S51 fastq_ori/ERR12712223_1.fastq fastq_ori/ERR12712223_2.fastq
F73312.S52 fastq_ori/ERR12712224_1.fastq fastq_ori/ERR12712224_2.fastq
F73312.S53 fastq_ori/ERR12712225_1.fastq fastq_ori/ERR12712225_2.fastq
F73312.S54 fastq_ori/ERR12712226_1.fastq fastq_ori/ERR12712226_2.fastq
F73312.S55 fastq_ori/ERR12712227_1.fastq fastq_ori/ERR12712227_2.fastq
F73312.S56 fastq_ori/ERR12712228_1.fastq fastq_ori/ERR12712228_2.fastq
F73312.S57 fastq_ori/ERR12712229_1.fastq fastq_ori/ERR12712229_2.fastq
F73312.S58 fastq_ori/ERR12712230_1.fastq fastq_ori/ERR12712230_2.fastq
F73312.S59 fastq_ori/ERR12712231_1.fastq fastq_ori/ERR12712231_2.fastq
F73312.S60 fastq_ori/ERR12712232_1.fastq fastq_ori/ERR12712232_2.fastq
F73312.S61 fastq_ori/ERR12712233_1.fastq fastq_ori/ERR12712233_2.fastq
F73312.S62 fastq_ori/ERR12712234_1.fastq fastq_ori/ERR12712234_2.fastq
F73312.S63 fastq_ori/ERR12712235_1.fastq fastq_ori/ERR12712235_2.fastq
F73312.S64 fastq_ori/ERR12712236_1.fastq fastq_ori/ERR12712236_2.fastq
F73312.S65 fastq_ori/ERR12712237_1.fastq fastq_ori/ERR12712237_2.fastq
F73312.S66 fastq_ori/ERR12712238_1.fastq fastq_ori/ERR12712238_2.fastq
F73312.S67 fastq_ori/ERR12712239_1.fastq fastq_ori/ERR12712239_2.fastq
F73312.S68 fastq_ori/ERR12712240_1.fastq fastq_ori/ERR12712240_2.fastq
F73312.S69 fastq_ori/ERR12712241_1.fastq fastq_ori/ERR12712241_2.fastq
F73312.S70 fastq_ori/ERR12712242_1.fastq fastq_ori/ERR12712242_2.fastq
F73312.S71 fastq_ori/ERR12712243_1.fastq fastq_ori/ERR12712243_2.fastq
F73312.S72 fastq_ori/ERR12712244_1.fastq fastq_ori/ERR12712244_2.fastq
F73312.S73 fastq_ori/ERR12712245_1.fastq fastq_ori/ERR12712245_2.fastq
F73312.S74 fastq_ori/ERR12712246_1.fastq fastq_ori/ERR12712246_2.fastq
F73312.S75 fastq_ori/ERR12712247_1.fastq fastq_ori/ERR12712247_2.fastq
F73312.S76 fastq_ori/ERR12712248_1.fastq fastq_ori/ERR12712248_2.fastq
F73312.S77 fastq_ori/ERR12712249_1.fastq fastq_ori/ERR12712249_2.fastq
F73312.S78 fastq_ori/ERR12712250_1.fastq fastq_ori/ERR12712250_2.fastq
F73312.S79 fastq_ori/ERR12712251_1.fastq fastq_ori/ERR12712251_2.fastq
F73312.S80 fastq_ori/ERR12712252_1.fastq fastq_ori/ERR12712252_2.fastq
F73312.S81 fastq_ori/ERR12712253_1.fastq fastq_ori/ERR12712253_2.fastq
F73312.S82 fastq_ori/ERR12712254_1.fastq fastq_ori/ERR12712254_2.fastq
F73312.S83 fastq_ori/ERR12712255_1.fastq fastq_ori/ERR12712255_2.fastq
F73312.S84 fastq_ori/ERR12712256_1.fastq fastq_ori/ERR12712256_2.fastq
F73312.S85 fastq_ori/ERR12712257_1.fastq fastq_ori/ERR12712257_2.fastq
F73312.S86 fastq_ori/ERR12712258_1.fastq fastq_ori/ERR12712258_2.fastq
F73312.S87 fastq_ori/ERR12712259_1.fastq fastq_ori/ERR12712259_2.fastq
F1043432.S01 fastq_ori/SRR26896019_1.fastq fastq_ori/SRR26896019_2.fastq
F1043432.S02 fastq_ori/SRR26896030_1.fastq fastq_ori/SRR26896030_2.fastq
F1043432.S03 fastq_ori/SRR26896041_1.fastq fastq_ori/SRR26896041_2.fastq
F1043432.S04 fastq_ori/SRR26896052_1.fastq fastq_ori/SRR26896052_2.fastq
F1043432.S05 fastq_ori/SRR26896054_1.fastq fastq_ori/SRR26896054_2.fastq
F1043432.S06 fastq_ori/SRR26896055_1.fastq fastq_ori/SRR26896055_2.fastq
F1043432.S07 fastq_ori/SRR26896056_1.fastq fastq_ori/SRR26896056_2.fastq
F1043432.S08 fastq_ori/SRR26896057_1.fastq fastq_ori/SRR26896057_2.fastq
F1043432.S09 fastq_ori/SRR26896058_1.fastq fastq_ori/SRR26896058_2.fastq
F1043432.S10 fastq_ori/SRR26896059_1.fastq fastq_ori/SRR26896059_2.fastq
F1043432.S11 fastq_ori/SRR26896060_1.fastq fastq_ori/SRR26896060_2.fastq
F1043432.S12 fastq_ori/SRR26896061_1.fastq fastq_ori/SRR26896061_2.fastq
F1043432.S13 fastq_ori/SRR26896062_1.fastq fastq_ori/SRR26896062_2.fastq
F1043432.S14 fastq_ori/SRR26896063_1.fastq fastq_ori/SRR26896063_2.fastq
F1043432.S15 fastq_ori/SRR26896064_1.fastq fastq_ori/SRR26896064_2.fastq
F1043432.S16 fastq_ori/SRR26896065_1.fastq fastq_ori/SRR26896065_2.fastq
F1043432.S17 fastq_ori/SRR26896066_1.fastq fastq_ori/SRR26896066_2.fastq
F1043432.S18 fastq_ori/SRR26896067_1.fastq fastq_ori/SRR26896067_2.fastq
F1043432.S19 fastq_ori/SRR26896068_1.fastq fastq_ori/SRR26896068_2.fastq
F1043432.S20 fastq_ori/SRR26896069_1.fastq fastq_ori/SRR26896069_2.fastq
F1043432.S21 fastq_ori/SRR26896070_1.fastq fastq_ori/SRR26896070_2.fastq
F1043432.S22 fastq_ori/SRR26896071_1.fastq fastq_ori/SRR26896071_2.fastq
F1043432.S23 fastq_ori/SRR26896072_1.fastq fastq_ori/SRR26896072_2.fastq
F1043432.S24 fastq_ori/SRR26896073_1.fastq fastq_ori/SRR26896073_2.fastq
F1043432.S25 fastq_ori/SRR26896074_1.fastq fastq_ori/SRR26896074_2.fastq
F1043432.S26 fastq_ori/SRR26896075_1.fastq fastq_ori/SRR26896075_2.fastq
F1043432.S27 fastq_ori/SRR26896076_1.fastq fastq_ori/SRR26896076_2.fastq
F1043432.S28 fastq_ori/SRR26896077_1.fastq fastq_ori/SRR26896077_2.fastq
F1043432.S29 fastq_ori/SRR26896078_1.fastq fastq_ori/SRR26896078_2.fastq
F1043432.S30 fastq_ori/SRR26896079_1.fastq fastq_ori/SRR26896079_2.fastq
F1043432.S31 fastq_ori/SRR26896080_1.fastq fastq_ori/SRR26896080_2.fastq
F1043432.S32 fastq_ori/SRR26896081_1.fastq fastq_ori/SRR26896081_2.fastq
F1043432.S33 fastq_ori/SRR26896082_1.fastq fastq_ori/SRR26896082_2.fastq
F1043432.S34 fastq_ori/SRR26896083_1.fastq fastq_ori/SRR26896083_2.fastq
F1043432.S35 fastq_ori/SRR26896084_1.fastq fastq_ori/SRR26896084_2.fastq
F1043432.S36 fastq_ori/SRR26896085_1.fastq fastq_ori/SRR26896085_2.fastq
F1043432.S37 fastq_ori/SRR26896086_1.fastq fastq_ori/SRR26896086_2.fastq
F1043432.S38 fastq_ori/SRR26896087_1.fastq fastq_ori/SRR26896087_2.fastq
F1043432.S39 fastq_ori/SRR26896088_1.fastq fastq_ori/SRR26896088_2.fastq
F1043432.S40 fastq_ori/SRR26896089_1.fastq fastq_ori/SRR26896089_2.fastq
F1043432.S41 fastq_ori/SRR26896090_1.fastq fastq_ori/SRR26896090_2.fastq
F1043432.S42 fastq_ori/SRR26896091_1.fastq fastq_ori/SRR26896091_2.fastq
F1043432.S43 fastq_ori/SRR26896092_1.fastq fastq_ori/SRR26896092_2.fastq
F1043432.S44 fastq_ori/SRR26896093_1.fastq fastq_ori/SRR26896093_2.fastq
F1043432.S45 fastq_ori/SRR26896094_1.fastq fastq_ori/SRR26896094_2.fastq
F1043432.S46 fastq_ori/SRR26896095_1.fastq fastq_ori/SRR26896095_2.fastq
F1043432.S47 fastq_ori/SRR26896096_1.fastq fastq_ori/SRR26896096_2.fastq
F1043432.S48 fastq_ori/SRR26896097_1.fastq fastq_ori/SRR26896097_2.fastq
F1043432.S49 fastq_ori/SRR26896098_1.fastq fastq_ori/SRR26896098_2.fastq
F1043432.S50 fastq_ori/SRR26896099_1.fastq fastq_ori/SRR26896099_2.fastq
F1043432.S51 fastq_ori/SRR26896100_1.fastq fastq_ori/SRR26896100_2.fastq
F1043432.S52 fastq_ori/SRR26896101_1.fastq fastq_ori/SRR26896101_2.fastq
F1043432.S53 fastq_ori/SRR26896102_1.fastq fastq_ori/SRR26896102_2.fastq
F1043432.S54 fastq_ori/SRR26896103_1.fastq fastq_ori/SRR26896103_2.fastq
F1043432.S55 fastq_ori/SRR26896104_1.fastq fastq_ori/SRR26896104_2.fastq
F1043432.S56 fastq_ori/SRR26896105_1.fastq fastq_ori/SRR26896105_2.fastq
F1043432.S57 fastq_ori/SRR26896106_1.fastq fastq_ori/SRR26896106_2.fastq
F1043432.S58 fastq_ori/SRR26896107_1.fastq fastq_ori/SRR26896107_2.fastq
F1043432.S59 fastq_ori/SRR26896108_1.fastq fastq_ori/SRR26896108_2.fastq
F1049117.S01 fastq_ori/SRR27100551_1.fastq fastq_ori/SRR27100551_2.fastq
F1049117.S02 fastq_ori/SRR27100552_1.fastq fastq_ori/SRR27100552_2.fastq
F1049117.S03 fastq_ori/SRR27100553_1.fastq fastq_ori/SRR27100553_2.fastq
F1049117.S04 fastq_ori/SRR27100554_1.fastq fastq_ori/SRR27100554_2.fastq
F1049117.S05 fastq_ori/SRR27100555_1.fastq fastq_ori/SRR27100555_2.fastq
F1049117.S06 fastq_ori/SRR27100556_1.fastq fastq_ori/SRR27100556_2.fastq
F1049117.S07 fastq_ori/SRR27100557_1.fastq fastq_ori/SRR27100557_2.fastq
F1049117.S08 fastq_ori/SRR27100558_1.fastq fastq_ori/SRR27100558_2.fastq
F1049117.S09 fastq_ori/SRR27100559_1.fastq fastq_ori/SRR27100559_2.fastq
F1049117.S10 fastq_ori/SRR27100560_1.fastq fastq_ori/SRR27100560_2.fastq
F1049117.S11 fastq_ori/SRR27100561_1.fastq fastq_ori/SRR27100561_2.fastq
F1049117.S12 fastq_ori/SRR27100562_1.fastq fastq_ori/SRR27100562_2.fastq
F1049117.S13 fastq_ori/SRR27100563_1.fastq fastq_ori/SRR27100563_2.fastq
F1049117.S14 fastq_ori/SRR27100564_1.fastq fastq_ori/SRR27100564_2.fastq
F1049117.S15 fastq_ori/SRR27100565_1.fastq fastq_ori/SRR27100565_2.fastq
F1049117.S16 fastq_ori/SRR27100566_1.fastq fastq_ori/SRR27100566_2.fastq
F1049117.S17 fastq_ori/SRR27100567_1.fastq fastq_ori/SRR27100567_2.fastq
F1049117.S18 fastq_ori/SRR27100568_1.fastq fastq_ori/SRR27100568_2.fastq
F1049117.S19 fastq_ori/SRR27100569_1.fastq fastq_ori/SRR27100569_2.fastq
F1049117.S20 fastq_ori/SRR27100570_1.fastq fastq_ori/SRR27100570_2.fastq
F1049117.S21 fastq_ori/SRR27100571_1.fastq fastq_ori/SRR27100571_2.fastq
F1049117.S22 fastq_ori/SRR27100572_1.fastq fastq_ori/SRR27100572_2.fastq
F1049117.S23 fastq_ori/SRR27100573_1.fastq fastq_ori/SRR27100573_2.fastq
F1049117.S24 fastq_ori/SRR27100574_1.fastq fastq_ori/SRR27100574_2.fastq
F1049117.S25 fastq_ori/SRR27100575_1.fastq fastq_ori/SRR27100575_2.fastq
F1049117.S26 fastq_ori/SRR27100576_1.fastq fastq_ori/SRR27100576_2.fastq
F1049117.S27 fastq_ori/SRR27100577_1.fastq fastq_ori/SRR27100577_2.fastq
F1049117.S28 fastq_ori/SRR27100578_1.fastq fastq_ori/SRR27100578_2.fastq
F1049117.S29 fastq_ori/SRR27100579_1.fastq fastq_ori/SRR27100579_2.fastq
F1049117.S30 fastq_ori/SRR27100580_1.fastq fastq_ori/SRR27100580_2.fastq
F1049117.S31 fastq_ori/SRR27100581_1.fastq fastq_ori/SRR27100581_2.fastq
F1049117.S32 fastq_ori/SRR27100582_1.fastq fastq_ori/SRR27100582_2.fastq
F1049117.S33 fastq_ori/SRR27100583_1.fastq fastq_ori/SRR27100583_2.fastq
F1049117.S34 fastq_ori/SRR27100584_1.fastq fastq_ori/SRR27100584_2.fastq
F1049117.S35 fastq_ori/SRR27100585_1.fastq fastq_ori/SRR27100585_2.fastq
F1049117.S36 fastq_ori/SRR27100586_1.fastq fastq_ori/SRR27100586_2.fastq
F1049117.S37 fastq_ori/SRR27100587_1.fastq fastq_ori/SRR27100587_2.fastq
F1049117.S38 fastq_ori/SRR27100588_1.fastq fastq_ori/SRR27100588_2.fastq
F1049117.S39 fastq_ori/SRR27100589_1.fastq fastq_ori/SRR27100589_2.fastq
F1049117.S40 fastq_ori/SRR27100590_1.fastq fastq_ori/SRR27100590_2.fastq
F1049117.S41 fastq_ori/SRR27100591_1.fastq fastq_ori/SRR27100591_2.fastq
F1049117.S42 fastq_ori/SRR27100592_1.fastq fastq_ori/SRR27100592_2.fastq
F1049117.S43 fastq_ori/SRR27100593_1.fastq fastq_ori/SRR27100593_2.fastq
F556311.S01 fastq_ori/SRR9821833_1.fastq fastq_ori/SRR9821833_2.fastq
F556311.S02 fastq_ori/SRR9821834_1.fastq fastq_ori/SRR9821834_2.fastq
F556311.S03 fastq_ori/SRR9821835_1.fastq fastq_ori/SRR9821835_2.fastq
F556311.S04 fastq_ori/SRR9821836_1.fastq fastq_ori/SRR9821836_2.fastq
F556311.S05 fastq_ori/SRR9821837_1.fastq fastq_ori/SRR9821837_2.fastq
F556311.S06 fastq_ori/SRR9821838_1.fastq fastq_ori/SRR9821838_2.fastq
F556311.S07 fastq_ori/SRR9821839_1.fastq fastq_ori/SRR9821839_2.fastq
F556311.S08 fastq_ori/SRR9821840_1.fastq fastq_ori/SRR9821840_2.fastq
F556311.S09 fastq_ori/SRR9821841_1.fastq fastq_ori/SRR9821841_2.fastq
F556311.S10 fastq_ori/SRR9821842_1.fastq fastq_ori/SRR9821842_2.fastq
F556311.S11 fastq_ori/SRR9821843_1.fastq fastq_ori/SRR9821843_2.fastq
F556311.S12 fastq_ori/SRR9821844_1.fastq fastq_ori/SRR9821844_2.fastq
F556311.S13 fastq_ori/SRR9821845_1.fastq fastq_ori/SRR9821845_2.fastq
F556311.S14 fastq_ori/SRR9821846_1.fastq fastq_ori/SRR9821846_2.fastq
F556311.S15 fastq_ori/SRR9821847_1.fastq fastq_ori/SRR9821847_2.fastq
F556311.S16 fastq_ori/SRR9821848_1.fastq fastq_ori/SRR9821848_2.fastq
F556311.S17 fastq_ori/SRR9821849_1.fastq fastq_ori/SRR9821849_2.fastq
F556311.S18 fastq_ori/SRR9821850_1.fastq fastq_ori/SRR9821850_2.fastq
F556311.S19 fastq_ori/SRR9821851_1.fastq fastq_ori/SRR9821851_2.fastq
F556311.S20 fastq_ori/SRR9821852_1.fastq fastq_ori/SRR9821852_2.fastq
F556311.S21 fastq_ori/SRR9821853_1.fastq fastq_ori/SRR9821853_2.fastq
F556311.S22 fastq_ori/SRR9821854_1.fastq fastq_ori/SRR9821854_2.fastq
F556311.S23 fastq_ori/SRR9821855_1.fastq fastq_ori/SRR9821855_2.fastq
F556311.S24 fastq_ori/SRR9821856_1.fastq fastq_ori/SRR9821856_2.fastq
F556311.S25 fastq_ori/SRR9821857_1.fastq fastq_ori/SRR9821857_2.fastq
F556311.S26 fastq_ori/SRR9821858_1.fastq fastq_ori/SRR9821858_2.fastq
F556311.S27 fastq_ori/SRR9821859_1.fastq fastq_ori/SRR9821859_2.fastq
F556311.S28 fastq_ori/SRR9821860_1.fastq fastq_ori/SRR9821860_2.fastq
F556311.S29 fastq_ori/SRR9821861_1.fastq fastq_ori/SRR9821861_2.fastq
F556311.S30 fastq_ori/SRR9821862_1.fastq fastq_ori/SRR9821862_2.fastq
F556311.S31 fastq_ori/SRR9821863_1.fastq fastq_ori/SRR9821863_2.fastq
F556311.S32 fastq_ori/SRR9821864_1.fastq fastq_ori/SRR9821864_2.fastq
F556311.S33 fastq_ori/SRR9821865_1.fastq fastq_ori/SRR9821865_2.fastq
F556311.S34 fastq_ori/SRR9821866_1.fastq fastq_ori/SRR9821866_2.fastq
F556311.S35 fastq_ori/SRR9821867_1.fastq fastq_ori/SRR9821867_2.fastq
F556311.S36 fastq_ori/SRR9821868_1.fastq fastq_ori/SRR9821868_2.fastq
F556311.S37 fastq_ori/SRR9821869_1.fastq fastq_ori/SRR9821869_2.fastq
F556311.S38 fastq_ori/SRR9821870_1.fastq fastq_ori/SRR9821870_2.fastq
F556311.S39 fastq_ori/SRR9821871_1.fastq fastq_ori/SRR9821871_2.fastq
F556311.S40 fastq_ori/SRR9821872_1.fastq fastq_ori/SRR9821872_2.fastq
F556311.S41 fastq_ori/SRR9821873_1.fastq fastq_ori/SRR9821873_2.fastq
F556311.S42 fastq_ori/SRR9821874_1.fastq fastq_ori/SRR9821874_2.fastq
F556311.S43 fastq_ori/SRR9821875_1.fastq fastq_ori/SRR9821875_2.fastq
F556311.S44 fastq_ori/SRR9821876_1.fastq fastq_ori/SRR9821876_2.fastq
F556311.S45 fastq_ori/SRR9821877_1.fastq fastq_ori/SRR9821877_2.fastq
F556311.S46 fastq_ori/SRR9821878_1.fastq fastq_ori/SRR9821878_2.fastq
F556311.S47 fastq_ori/SRR9821879_1.fastq fastq_ori/SRR9821879_2.fastq
F556311.S48 fastq_ori/SRR9821880_1.fastq fastq_ori/SRR9821880_2.fastq
F556311.S49 fastq_ori/SRR9821881_1.fastq fastq_ori/SRR9821881_2.fastq
F556311.S50 fastq_ori/SRR9821882_1.fastq fastq_ori/SRR9821882_2.fastq
F556311.S51 fastq_ori/SRR9821883_1.fastq fastq_ori/SRR9821883_2.fastq
F556311.S52 fastq_ori/SRR9821884_1.fastq fastq_ori/SRR9821884_2.fastq
F556311.S53 fastq_ori/SRR9821885_1.fastq fastq_ori/SRR9821885_2.fastq
F556311.S54 fastq_ori/SRR9821886_1.fastq fastq_ori/SRR9821886_2.fastq
F556311.S55 fastq_ori/SRR9821887_1.fastq fastq_ori/SRR9821887_2.fastq
F556311.S56 fastq_ori/SRR9821888_1.fastq fastq_ori/SRR9821888_2.fastq
F556311.S57 fastq_ori/SRR9821889_1.fastq fastq_ori/SRR9821889_2.fastq
F556311.S58 fastq_ori/SRR9821890_1.fastq fastq_ori/SRR9821890_2.fastq
F556311.S59 fastq_ori/SRR9821891_1.fastq fastq_ori/SRR9821891_2.fastq
F556311.S60 fastq_ori/SRR9821892_1.fastq fastq_ori/SRR9821892_2.fastq
F598825.S01 fastq_ori/SRR10849321_1.fastq fastq_ori/SRR10849321_2.fastq
F598825.S02 fastq_ori/SRR10849322_1.fastq fastq_ori/SRR10849322_2.fastq
F598825.S03 fastq_ori/SRR10849323_1.fastq fastq_ori/SRR10849323_2.fastq
F598825.S04 fastq_ori/SRR10849324_1.fastq fastq_ori/SRR10849324_2.fastq
F598825.S05 fastq_ori/SRR10849325_1.fastq fastq_ori/SRR10849325_2.fastq
F598825.S06 fastq_ori/SRR10849326_1.fastq fastq_ori/SRR10849326_2.fastq
F598825.S07 fastq_ori/SRR10849327_1.fastq fastq_ori/SRR10849327_2.fastq
F598825.S08 fastq_ori/SRR10849328_1.fastq fastq_ori/SRR10849328_2.fastq
F598825.S09 fastq_ori/SRR10849329_1.fastq fastq_ori/SRR10849329_2.fastq
F598825.S10 fastq_ori/SRR10849330_1.fastq fastq_ori/SRR10849330_2.fastq
F598825.S11 fastq_ori/SRR10849331_1.fastq fastq_ori/SRR10849331_2.fastq
F598825.S12 fastq_ori/SRR10849332_1.fastq fastq_ori/SRR10849332_2.fastq
F598825.S13 fastq_ori/SRR10849333_1.fastq fastq_ori/SRR10849333_2.fastq
F598825.S14 fastq_ori/SRR10849334_1.fastq fastq_ori/SRR10849334_2.fastq
F598825.S15 fastq_ori/SRR10849335_1.fastq fastq_ori/SRR10849335_2.fastq
F598825.S16 fastq_ori/SRR10849336_1.fastq fastq_ori/SRR10849336_2.fastq
F598825.S17 fastq_ori/SRR10849337_1.fastq fastq_ori/SRR10849337_2.fastq
F598825.S18 fastq_ori/SRR10849338_1.fastq fastq_ori/SRR10849338_2.fastq
F598825.S19 fastq_ori/SRR10849339_1.fastq fastq_ori/SRR10849339_2.fastq
F598825.S20 fastq_ori/SRR10849340_1.fastq fastq_ori/SRR10849340_2.fastq
F598825.S21 fastq_ori/SRR10849341_1.fastq fastq_ori/SRR10849341_2.fastq
F598825.S22 fastq_ori/SRR10849342_1.fastq fastq_ori/SRR10849342_2.fastq
F598825.S23 fastq_ori/SRR10849343_1.fastq fastq_ori/SRR10849343_2.fastq
F598825.S24 fastq_ori/SRR10849344_1.fastq fastq_ori/SRR10849344_2.fastq
F598825.S25 fastq_ori/SRR10849345_1.fastq fastq_ori/SRR10849345_2.fastq
F598825.S26 fastq_ori/SRR10849346_1.fastq fastq_ori/SRR10849346_2.fastq
F598825.S27 fastq_ori/SRR10849347_1.fastq fastq_ori/SRR10849347_2.fastq
F598825.S28 fastq_ori/SRR10849348_1.fastq fastq_ori/SRR10849348_2.fastq
F598825.S29 fastq_ori/SRR10849349_1.fastq fastq_ori/SRR10849349_2.fastq
F598825.S30 fastq_ori/SRR10849350_1.fastq fastq_ori/SRR10849350_2.fastq
F756771.S01 fastq_ori/SRR15560286_1.fastq fastq_ori/SRR15560286_2.fastq
F756771.S02 fastq_ori/SRR15560287_1.fastq fastq_ori/SRR15560287_2.fastq
F756771.S03 fastq_ori/SRR15560288_1.fastq fastq_ori/SRR15560288_2.fastq
F756771.S04 fastq_ori/SRR15560289_1.fastq fastq_ori/SRR15560289_2.fastq
F756771.S05 fastq_ori/SRR15560290_1.fastq fastq_ori/SRR15560290_2.fastq
F756771.S06 fastq_ori/SRR15560291_1.fastq fastq_ori/SRR15560291_2.fastq
F756771.S07 fastq_ori/SRR15560292_1.fastq fastq_ori/SRR15560292_2.fastq
F756771.S08 fastq_ori/SRR15560293_1.fastq fastq_ori/SRR15560293_2.fastq
F756771.S09 fastq_ori/SRR15560294_1.fastq fastq_ori/SRR15560294_2.fastq
F756771.S10 fastq_ori/SRR15560295_1.fastq fastq_ori/SRR15560295_2.fastq
F756771.S11 fastq_ori/SRR15560296_1.fastq fastq_ori/SRR15560296_2.fastq
F756771.S12 fastq_ori/SRR15560297_1.fastq fastq_ori/SRR15560297_2.fastq
F756771.S13 fastq_ori/SRR15560298_1.fastq fastq_ori/SRR15560298_2.fastq
F756771.S14 fastq_ori/SRR15560299_1.fastq fastq_ori/SRR15560299_2.fastq
F756771.S15 fastq_ori/SRR15560300_1.fastq fastq_ori/SRR15560300_2.fastq
F756771.S16 fastq_ori/SRR15560301_1.fastq fastq_ori/SRR15560301_2.fastq
F756771.S17 fastq_ori/SRR15560302_1.fastq fastq_ori/SRR15560302_2.fastq
F756771.S18 fastq_ori/SRR15560303_1.fastq fastq_ori/SRR15560303_2.fastq
F756771.S19 fastq_ori/SRR15560304_1.fastq fastq_ori/SRR15560304_2.fastq
F756771.S20 fastq_ori/SRR15560305_1.fastq fastq_ori/SRR15560305_2.fastq
F756771.S21 fastq_ori/SRR15560306_1.fastq fastq_ori/SRR15560306_2.fastq
F756771.S22 fastq_ori/SRR15560307_1.fastq fastq_ori/SRR15560307_2.fastq
F756771.S23 fastq_ori/SRR15560308_1.fastq fastq_ori/SRR15560308_2.fastq
F756771.S24 fastq_ori/SRR15560309_1.fastq fastq_ori/SRR15560309_2.fastq
F756771.S25 fastq_ori/SRR15560310_1.fastq fastq_ori/SRR15560310_2.fastq
F756771.S26 fastq_ori/SRR15560311_1.fastq fastq_ori/SRR15560311_2.fastq
F756771.S27 fastq_ori/SRR15560312_1.fastq fastq_ori/SRR15560312_2.fastq
F756771.S28 fastq_ori/SRR15560313_1.fastq fastq_ori/SRR15560313_2.fastq
F756771.S29 fastq_ori/SRR15560314_1.fastq fastq_ori/SRR15560314_2.fastq
F756771.S30 fastq_ori/SRR15560315_1.fastq fastq_ori/SRR15560315_2.fastq
F756771.S31 fastq_ori/SRR15560316_1.fastq fastq_ori/SRR15560316_2.fastq
F756771.S32 fastq_ori/SRR15560317_1.fastq fastq_ori/SRR15560317_2.fastq
F756771.S33 fastq_ori/SRR15560318_1.fastq fastq_ori/SRR15560318_2.fastq
F266382.S01 fastq_ori/SRR2064219.fastq 
F266382.S02 fastq_ori/SRR2064220.fastq 
F266382.S03 fastq_ori/SRR2064221.fastq 
F266382.S04 fastq_ori/SRR2064222.fastq 
F266382.S05 fastq_ori/SRR2064223.fastq 
F266382.S06 fastq_ori/SRR2064224.fastq 
F266382.S07 fastq_ori/SRR2064225.fastq 
F266382.S08 fastq_ori/SRR2064226.fastq 
F266382.S09 fastq_ori/SRR2064227.fastq 
F266382.S10 fastq_ori/SRR2064228.fastq 
F266382.S11 fastq_ori/SRR2064229.fastq 
F266382.S12 fastq_ori/SRR2064230.fastq 
F266382.S13 fastq_ori/SRR2064231.fastq 
F266382.S14 fastq_ori/SRR2064232.fastq 
F266382.S15 fastq_ori/SRR2064233.fastq 
F266382.S16 fastq_ori/SRR2064234.fastq 
F266382.S17 fastq_ori/SRR2064235.fastq 
F266382.S18 fastq_ori/SRR2064236.fastq 
F266382.S19 fastq_ori/SRR2064237.fastq 
F266382.S20 fastq_ori/SRR2064238.fastq 
F266382.S21 fastq_ori/SRR2064239.fastq 
F266382.S22 fastq_ori/SRR2064240.fastq 
F266382.S23 fastq_ori/SRR2064241.fastq 
F266382.S24 fastq_ori/SRR2064242.fastq 
F266382.S25 fastq_ori/SRR2064243.fastq 
F266382.S26 fastq_ori/SRR2064244.fastq 
F266382.S27 fastq_ori/SRR2064245.fastq 
F266382.S28 fastq_ori/SRR2064246.fastq 
F266382.S29 fastq_ori/SRR2064247.fastq 
F266382.S30 fastq_ori/SRR2064248.fastq 
F266382.S31 fastq_ori/SRR2064249.fastq 
F266382.S32 fastq_ori/SRR2064250.fastq 
F266382.S33 fastq_ori/SRR2064251.fastq 
F266382.S34 fastq_ori/SRR2064252.fastq 
F266382.S35 fastq_ori/SRR2064253.fastq 
F266382.S36 fastq_ori/SRR2064254.fastq 
F266382.S37 fastq_ori/SRR2064255.fastq 
F266382.S38 fastq_ori/SRR2064256.fastq 
F266382.S39 fastq_ori/SRR2064257.fastq 
F266382.S40 fastq_ori/SRR2064258.fastq 
F266382.S41 fastq_ori/SRR2064259.fastq 
F266382.S42 fastq_ori/SRR2064260.fastq 
F266382.S43 fastq_ori/SRR2064261.fastq 
F266382.S44 fastq_ori/SRR2064262.fastq 
F266382.S45 fastq_ori/SRR2064263.fastq 
F266382.S46 fastq_ori/SRR2064264.fastq 
F266382.S47 fastq_ori/SRR2064265.fastq 
F266382.S48 fastq_ori/SRR2064266.fastq 
F266382.S49 fastq_ori/SRR2064267.fastq 
F266382.S50 fastq_ori/SRR2064268.fastq 
F266382.S51 fastq_ori/SRR2064269.fastq 
F266382.S52 fastq_ori/SRR2064270.fastq 
F266382.S53 fastq_ori/SRR2064271.fastq 
F266382.S54 fastq_ori/SRR2064272.fastq 
F266382.S55 fastq_ori/SRR2064273.fastq 
F266382.S56 fastq_ori/SRR2064274.fastq 
F266382.S57 fastq_ori/SRR2064275.fastq 
F266382.S58 fastq_ori/SRR2064276.fastq 
F266382.S59 fastq_ori/SRR2064277.fastq 
F266382.S60 fastq_ori/SRR2064278.fastq 
F295501.S01 fastq_ori/SRR2914373.fastq 
F295501.S02 fastq_ori/SRR2914374.fastq 
F295501.S03 fastq_ori/SRR2914375.fastq 
F295501.S04 fastq_ori/SRR2914376.fastq 
F295501.S05 fastq_ori/SRR2914377.fastq 
F295501.S06 fastq_ori/SRR2914378.fastq 
F295501.S07 fastq_ori/SRR2914379.fastq 
F295501.S08 fastq_ori/SRR2914380.fastq 
F295501.S09 fastq_ori/SRR2914381.fastq 
F295501.S10 fastq_ori/SRR2914382.fastq 
F295501.S11 fastq_ori/SRR2914383.fastq 
F295501.S12 fastq_ori/SRR2914384.fastq 
F295501.S13 fastq_ori/SRR2914385.fastq 
F295501.S14 fastq_ori/SRR2989657.fastq

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.

Raw sequence data download link:

VI. Analysis - DADA2 Read Processing

What is DADA2?

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.

DADA2 Software Package is available as an R package at : https://benjjneb.github.io/dada2/index.html

References

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”.

Quality plots for all samples:

quality_plots_1-20.pdf

quality_plots_21-40.pdf

quality_plots_41-60.pdf

quality_plots_61-80.pdf

quality_plots_81-87.pdf

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	251	241	231	221	211	201
251	73.88%	74.07%	74.42%	74.60%	74.86%	75.16%
241	74.21%	74.38%	74.81%	74.98%	75.18%	75.44%
231	74.73%	74.88%	75.36%	75.45%	75.58%	75.87%
221	75.10%	75.27%	75.75%	75.91%	76.02%	76.34%
211	75.41%	75.58%	76.12%	76.39%	76.56%	76.77%
201	75.74%	75.94%	76.40%	77.01%	77.21%	77.43%

Based on the above result, the trim length combination of R1 = 201 bases and R2 = 201 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	F73312.S01	F73312.S02	F73312.S03	F73312.S04	F73312.S05	F73312.S06	F73312.S07	F73312.S08	F73312.S09	F73312.S10	F73312.S11	F73312.S12	F73312.S13	F73312.S14	F73312.S15	F73312.S16	F73312.S17	F73312.S18	F73312.S19	F73312.S20	F73312.S21	F73312.S22	F73312.S23	F73312.S24	F73312.S25	F73312.S26	F73312.S27	F73312.S28	F73312.S29	F73312.S30	F73312.S31	F73312.S32	F73312.S33	F73312.S34	F73312.S35	F73312.S36	F73312.S37	F73312.S38	F73312.S39	F73312.S40	F73312.S41	F73312.S42	F73312.S43	F73312.S44	F73312.S45	F73312.S46	F73312.S47	F73312.S48	F73312.S49	F73312.S50	F73312.S51	F73312.S52	F73312.S53	F73312.S54	F73312.S55	F73312.S56	F73312.S57	F73312.S58	F73312.S59	F73312.S60	F73312.S61	F73312.S62	F73312.S63	F73312.S64	F73312.S65	F73312.S66	F73312.S67	F73312.S68	F73312.S69	F73312.S70	F73312.S71	F73312.S72	F73312.S73	F73312.S74	F73312.S75	F73312.S76	F73312.S77	F73312.S78	F73312.S79	F73312.S80	F73312.S81	F73312.S82	F73312.S83	F73312.S84	F73312.S85	F73312.S86	F73312.S87	Row Sum	Percentage
input	95,800	100,468	136,548	313,320	369,714	169,333	83,819	33,829	95,795	86,433	225,056	184,006	55,775	128,465	162,618	278,584	97,103	163,072	189,048	137,402	78,112	66,811	100,229	90,460	207,555	122,252	45,372	96,132	80,547	147,204	141,035	40,854	168,464	126,017	95,876	170,977	148,890	139,297	44,165	128,654	72,563	131,391	62,772	171,469	165,234	155,640	22,714	162,458	65,419	112,752	99,049	144,183	134,470	124,736	42,842	135,104	95,271	122,452	78,891	141,660	134,833	131,958	46,886	84,924	249,816	193,197	347,518	311,635	332,389	60,935	349,962	216,528	70,843	67,635	117,808	98,560	104,450	29,024	96,210	58,900	111,373	155,357	138,234	157,712	138,621	163,568	124,773	11,679,810	100.00%
filtered	95,800	100,463	136,546	313,316	369,709	169,331	83,818	33,827	95,793	86,431	225,051	184,001	55,774	128,462	162,615	278,583	97,101	163,065	189,045	137,398	78,109	66,811	100,229	90,458	207,550	122,251	45,372	96,132	80,544	147,203	141,031	40,851	168,461	126,016	95,874	170,973	148,888	139,296	44,165	128,652	72,562	131,387	62,771	171,468	165,227	155,638	22,714	162,456	65,418	112,752	99,046	144,181	134,470	124,735	42,842	135,098	95,270	122,448	78,890	141,657	134,830	131,957	46,885	84,923	249,813	193,193	347,506	311,632	332,381	60,934	349,951	216,527	70,839	67,633	117,805	98,559	104,450	29,022	96,207	58,900	111,370	155,356	138,232	157,711	138,619	163,567	124,773	11,679,600	100.00%
denoisedF	91,986	98,597	133,801	305,182	359,141	165,527	81,304	32,204	92,906	83,054	216,493	175,759	51,100	122,218	155,074	269,894	91,092	156,868	181,261	131,123	75,509	64,062	97,859	87,605	199,607	115,637	43,739	93,519	78,164	144,208	137,499	38,626	164,868	123,064	92,684	167,621	146,111	136,317	41,210	125,313	69,981	127,907	60,258	168,230	161,648	151,709	20,590	158,884	62,880	110,052	96,365	141,341	131,832	122,683	41,040	132,366	92,845	119,680	76,059	138,696	132,474	129,308	44,280	82,709	241,821	184,210	337,387	303,633	322,864	54,740	340,156	208,194	68,863	65,149	115,288	96,550	102,061	27,148	93,801	56,968	108,579	152,041	135,336	153,226	135,388	160,261	121,193	11,326,480	96.97%
denoisedR	93,726	98,572	133,529	304,935	359,480	165,698	81,420	32,682	93,232	83,694	217,320	176,475	53,215	124,217	157,154	270,578	93,018	157,191	183,571	132,999	75,595	65,062	97,859	87,484	200,546	117,994	43,688	93,593	78,353	144,192	137,289	39,633	164,645	122,948	93,833	166,867	145,957	135,855	42,601	125,650	70,752	128,037	61,166	167,755	161,882	151,522	20,578	158,823	63,850	109,937	96,904	140,604	131,552	122,161	41,563	132,330	93,321	119,584	77,012	138,565	132,129	128,718	45,592	83,085	242,613	188,270	338,171	303,793	322,909	58,760	340,649	211,217	68,868	65,489	115,085	96,453	101,943	28,044	93,817	57,411	108,415	151,772	135,062	153,999	135,652	160,226	122,080	11,370,470	97.35%
merged	85,705	92,831	125,418	284,823	333,660	154,934	74,530	28,626	85,096	75,510	197,844	157,601	43,650	112,168	140,804	248,641	80,053	143,460	167,111	119,170	69,228	58,586	91,055	80,312	183,155	104,964	39,427	85,696	71,815	134,616	126,410	34,622	154,530	114,177	86,520	157,072	136,604	128,154	35,120	117,641	64,416	119,921	54,292	158,500	152,184	140,903	17,122	148,859	58,940	102,703	90,726	131,909	124,260	116,030	37,434	125,072	86,503	111,085	70,927	129,151	124,325	121,653	39,822	77,082	224,025	168,840	315,324	283,329	298,606	46,943	315,860	194,041	63,604	59,103	106,694	90,881	94,755	24,524	87,222	52,413	100,588	143,320	125,989	141,284	127,447	150,106	113,131	10,493,187	89.84%
nonchim	68,775	74,817	105,760	219,069	268,019	127,957	63,465	26,365	66,948	66,994	168,492	135,453	40,446	101,356	122,150	210,045	73,426	123,384	143,743	105,406	60,768	50,664	78,506	68,361	153,483	94,196	34,723	73,449	61,581	109,218	102,802	30,763	119,634	94,915	69,936	120,564	111,179	106,163	32,693	89,634	54,331	99,032	47,029	126,939	122,931	119,966	16,497	117,525	49,176	82,155	74,661	106,013	105,538	89,758	33,303	98,964	73,068	95,694	60,502	107,456	101,490	95,003	36,068	61,487	187,200	139,185	256,273	238,415	229,833	41,469	250,257	154,072	52,730	53,064	87,940	69,623	77,714	22,390	72,091	42,916	79,366	113,585	105,197	111,815	99,963	123,768	94,037	8,652,791	74.08%

This table can be downloaded as an Excel table below:

5. DADA2 Amplicon Sequence Variants (ASVs). A total of 8296 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 table can be downloaded from this link:

Sample Meta Information

Download Sample Meta Information

#SampleID	Group
DGP103-13-M0	DGP103
DGP103-13-S0	DGP103
DGP103-19-D2	DGP103
DGP103-30-D0	DGP103
DGP106-04-D3	DGP106
DGP106-13-D2	DGP106
DGP106-20-M3	DGP106
DGP106-28-S3	DGP106
DGP107-03-D0	DGP107
DGP107-29-S2	DGP107
DGP107-30-S1	DGP107
DGP108-21-S2	DGP108
DGP108-30-D0	DGP108
DGP108-30-D2	DGP108
DGP114-20-M0	DGP116
DGP116-07-D0	DGP116
DGP116-08-D0	DGP116
DGP118-06-S0	DGP118
DGP118-06-S2	DGP118
DGP118-14-D2	DGP118

ASV Read Counts by Samples

#Sample ID	Read Count
DGP103-13-S0	84
DGP107-29-S2	109
DGP107-30-S1	3,020
DGP108-21-S2	4,530
DGP106-04-D3	5,338
DGP107-03-D0	5,847
DGP106-13-D2	6,245
DGP118-14-D2	7,394
DGP108-30-D0	7,867
DGP116-07-D0	8,209
DGP108-30-D2	8,938
DGP116-08-D0	9,110
DGP106-20-M3	9,521
DGP114-20-M0	10,208
DGP103-30-D0	11,226
DGP106-28-S3	13,146
DGP118-06-S2	13,183
DGP103-19-D2	13,946
DGP103-13-M0	18,718
DGP118-06-S0	31,655

VII. Analysis - Read Taxonomy Assignment

Read Taxonomy Assignment - Methods

The close-reference taxonomy assignment of the ASV sequences using BLASTN is based on the algorithm published by Al-Hebshi et. al. (2015)[2].

The species-level, open-reference 16S rRNA NGS reads taxonomy assignment pipeline

Version 20210310a

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%(>=18 reads)
A	Total reads	188,294	188,294
B	Total assigned reads	186,053	186,053
C	Assigned reads in species with read count < MPC	0	515
D	Assigned reads in samples with read count < 500	188	188
E	Total samples	20	20
F	Samples with reads >= 500	18	18
G	Samples with reads < 500	2	2
H	Total assigned reads used for analysis (B-C-D)	185,865	185,350
I	Reads assigned to single species	182,621	182,135
J	Reads assigned to multiple species	1,285	1,256
K	Reads assigned to novel species	1,959	1,959
L	Total number of species	362	294
M	Number of single species	348	283
N	Number of multi-species	9	6
O	Number of novel species	5	5
P	Total unassigned reads	2,241	2,241
Q	Chimeric reads	0	0
R	Reads without BLASTN hits	0	0
S	Others: short, low quality, singletons, etc.	2,241	2,241
	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.

SPID	Taxonomy	DGP103-13-M0	DGP103-13-S0	DGP103-19-D2	DGP103-30-D0	DGP106-04-D3	DGP106-13-D2	DGP106-20-M3	DGP106-28-S3	DGP107-03-D0	DGP107-29-S2	DGP107-30-S1	DGP108-21-S2	DGP108-30-D0	DGP108-30-D2	DGP114-20-M0	DGP116-07-D0	DGP116-08-D0	DGP118-06-S0	DGP118-06-S2	DGP118-14-D2
SP1	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp._oral_taxon_300	0	0	0	0	5	8	0	0	12	0	0	14	0	0	0	41	53	7	0	0
SP10	Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;concisus	56	0	14	5	9	32	64	116	0	0	11	12	0	10	0	0	0	17	21	0
SP100	Bacteria;SR1;SR1_[C-1];SR1_[O-1];SR1_[F-1];SR1_[G-1];sp._oral_taxon_345	0	0	0	0	0	0	10	0	54	0	0	0	0	0	0	0	0	12	322	24
SP101	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;sp._oral_taxon_170	149	0	0	19	0	0	0	17	0	0	0	0	0	0	0	0	0	18	0	0
SP103	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;sp._oral_taxon_913	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	6	35	26	0
SP104	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;infantis	34	0	0	0	0	0	0	0	0	0	168	0	0	94	0	0	0	0	0	0
SP105	Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;aphrophilus	0	0	0	0	0	17	8	0	0	0	50	0	0	0	0	0	0	33	0	0
SP107	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Bergeyella;sp._oral_taxon_322	16	4	34	15	7	9	53	34	0	0	0	0	0	0	16	0	0	0	7	12
SP108	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;socranskii	0	0	0	0	0	0	0	0	0	0	0	18	6	0	0	0	31	47	30	10
SP109	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-1];sp._oral_taxon_952	50	0	74	0	29	52	149	0	0	0	0	0	0	0	0	8	0	184	72	0
SP11	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;oris	0	0	191	419	258	42	185	751	39	0	0	25	78	140	0	268	118	667	0	13
SP110	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;sp._oral_taxon_203	0	0	0	0	0	0	0	0	201	0	33	0	0	0	0	688	165	1459	48	57
SP111	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp._oral_taxon_317	0	0	16	33	0	0	0	20	0	0	0	50	75	15	0	40	0	131	52	29
SP112	Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp._oral_taxon_949	0	0	103	0	0	0	9	0	0	0	0	0	0	0	8	0	0	0	0	0
SP113	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_230	0	0	0	0	0	0	10	10	0	0	0	0	0	0	0	0	0	5	49	3
SP114	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp._oral_taxon_336	85	0	160	197	0	5	0	33	4	0	0	0	0	0	0	0	0	0	0	0
SP115	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;artemidis	0	0	0	0	0	2	0	0	0	0	0	10	0	6	0	0	0	0	0	0
SP116	Bacteria;Synergistetes;Synergistia;Synergistales;Synergistaceae;Fretibacterium;sp._oral_taxon_362	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	37	0	25
SP117	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;flavescens\|subflava	0	0	13	0	0	58	0	0	0	0	10	0	16	24	0	14	1	6	13	192
SP119	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;intermedia	0	0	5	0	0	0	0	22	0	0	0	0	0	0	0	0	0	21	85	189
SP12	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp._oral_taxon_304	0	0	0	0	0	0	0	0	0	0	0	0	32	0	0	0	0	44	136	166
SP120	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp._oral_taxon_326	0	0	47	0	21	70	50	0	0	0	0	0	0	0	0	0	0	0	0	0
SP121	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Filifactor;alocis	0	0	14	22	0	41	4	4	62	0	0	0	35	16	0	0	0	531	182	191
SP122	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;sp._oral_taxon_912	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8	21	13	12	0
SP123	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp._oral_taxon_431	12	0	0	0	0	0	0	0	0	0	76	0	6	0	0	0	0	0	0	0
SP124	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;forsythia	0	0	12	0	0	18	0	3	68	0	0	25	47	36	0	299	478	1448	145	133
SP125	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-7];[Eubacterium]_yurii_subsp._schtitka	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	869	9	16
SP126	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;veroralis	0	0	37	0	11	0	10	0	50	0	0	0	0	0	0	0	0	0	0	0
SP127	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Veillonellaceae_[G-1];sp._oral_taxon_150	0	0	0	0	0	0	0	0	0	0	0	24	0	0	0	7	13	0	0	0
SP128	Bacteria;Synergistetes;Synergistia;Synergistales;Synergistaceae;Fretibacterium;sp._oral_taxon_359	0	0	0	0	0	0	0	0	0	0	0	28	28	31	0	0	0	0	29	0
SP129	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;pleuritidis	0	0	77	474	0	47	27	28	0	0	0	0	0	0	0	0	0	0	0	0
SP13	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;sp._oral_taxon_175	55	0	0	0	7	0	13	0	0	0	0	6	4	33	75	13	7	11	0	0
SP130	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;constellatus	0	0	32	38	0	0	0	26	14	0	0	13	0	84	0	19	25	0	0	0
SP131	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;oralis	21	0	14	0	0	0	0	0	0	0	0	0	0	0	0	0	0	10	0	0
SP132	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Micrococcaceae;Rothia;mucilaginosa	50	0	12	0	36	10	7	8	0	0	282	0	13	40	28	0	0	0	7	10
SP133	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp._oral_taxon_058	301	15	63	305	27	27	137	10	0	0	0	0	0	6	111	12	0	0	0	32
SP134	Bacteria;Firmicutes;Bacilli;Bacillales;Gemellaceae;Gemella;morbillorum	0	0	42	12	17	24	64	17	0	0	0	23	66	384	7	11	5	29	32	30
SP135	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Megasphaera;micronuciformis	16	0	11	0	44	7	8	0	0	0	0	0	15	0	0	0	0	0	0	0
SP136	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;gingivalis	13	0	14	0	40	14	85	56	0	0	22	0	7	13	17	11	8	0	9	0
SP137	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;sp._oral_taxon_089	0	0	0	9	0	0	0	0	14	0	0	0	0	0	0	0	0	0	0	0
SP139	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-1];sp._oral_taxon_349	0	0	0	3	0	50	0	23	0	0	0	5	9	7	0	152	134	221	210	22
SP140	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;sp._oral_taxon_278	0	0	0	0	0	0	0	0	39	0	0	0	0	0	0	0	0	12	0	0
SP141	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-2];sp._oral_taxon_350	0	0	0	0	0	223	9	14	0	0	0	0	0	0	0	0	0	0	0	0
SP142	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;gingivalis	21	0	0	2	0	0	0	0	1148	0	8	0	0	0	0	707	2883	3555	3090	2378
SP143	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;maltophilum	0	0	0	0	0	0	0	0	9	0	0	0	0	15	0	24	32	49	17	8
SP144	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;mitis	609	0	0	96	0	6	182	0	0	0	0	100	127	515	351	0	0	0	41	54
SP146	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_237	0	0	0	0	0	0	0	0	0	0	0	27	82	31	0	0	0	315	123	164
SP147	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetales_[F];Actinomycetales_[G];sp._Oral_Taxon_C05	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	12	12	0	0	0
SP148	Bacteria;Bacteroidetes;Sphingobacteriia;Sphingobacteriales;Sphingobacteriaceae;Sphingobacterium;multivorum	0	0	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	40	0	0
SP149	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;periodonticum	0	0	0	0	0	0	0	0	0	0	0	0	36	0	0	0	0	75	358	24
SP15	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp._oral_taxon_443	0	0	0	0	0	7	0	0	32	0	0	0	0	0	0	0	0	9	11	9
SP150	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter;johnsonii	0	18	25	455	17	7	0	11	0	0	0	0	55	40	0	0	0	338	0	0
SP151	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sp._oral_taxon_138	0	0	6	0	0	0	10	0	9	0	0	0	27	0	0	0	0	19	8	0
SP152	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;sp._oral_taxon_916	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	31	0
SP153	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-7];sp._oral_taxon_081	0	0	0	0	0	3	0	5	11	0	0	0	0	0	0	0	0	108	49	6
SP154	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_257	0	0	0	0	0	0	0	6	0	0	0	0	0	0	0	0	0	164	14	37
SP155	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;oulorum	66	0	88	33	133	9	31	303	0	0	0	16	112	51	0	19	54	10	0	0
SP156	Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;showae	4	0	45	0	0	97	119	10	12	0	0	26	157	19	0	0	0	35	30	0
SP157	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptoniphilaceae;Parvimonas;sp._oral_taxon_110	0	0	11	0	23	9	0	0	0	0	285	0	0	0	0	18	0	0	0	0
SP158	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp._oral_taxon_412	83	0	214	24	20	0	0	90	0	0	0	0	0	0	12	18	9	0	0	0
SP159	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;oralis	124	0	7	51	148	16	88	302	0	0	0	0	9	0	126	12	0	0	0	0
SP16	Bacteria;Actinobacteria;Actinobacteria;Corynebacteriales;Corynebacteriaceae;Corynebacterium;durum	116	0	0	0	0	0	7	0	0	0	0	0	0	0	53	6	0	0	0	0
SP160	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Pseudomonadaceae;Pseudomonas;pseudoalcaligenes	0	0	20	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
SP161	Bacteria;Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Ruminococcaceae_[G-1];sp._oral_taxon_075	24	0	158	12	17	0	84	75	157	0	0	0	30	0	0	0	0	16	6	0
SP162	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Eikenella;corrodens	0	0	5	0	0	0	0	0	0	0	0	8	21	8	0	26	0	128	0	0
SP163	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;disiens	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	7	20	0	0	0
SP164	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp._oral_taxon_526	0	0	0	0	0	0	0	0	18	0	0	0	0	22	0	0	0	15	23	20
SP165	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;medium	0	0	12	24	0	0	0	0	8	0	0	0	0	0	0	0	0	95	68	28
SP168	Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;rectus	0	0	54	103	0	37	0	0	0	0	0	0	0	0	0	0	0	187	23	91
SP169	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;sp._oral_taxon_286	6	3	83	0	0	0	15	0	30	0	0	95	518	222	3	0	0	14	0	0
SP17	Bacteria;Actinobacteria;Actinobacteria;Propionibacteriales;Propionibacteriaceae;Propionibacterium;sp._oral_taxon_194	19	0	7	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
SP170	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Micrococcaceae;Micrococcus;luteus_Oral_Taxon_H68	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	49	0	0
SP171	Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp._oral_taxon_458	0	0	41	0	0	0	0	0	0	0	0	0	183	0	8	0	0	0	0	0
SP172	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;pallens	0	0	0	0	0	0	7	0	0	0	0	0	0	32	0	0	0	0	0	0
SP173	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;buccalis	9	0	4093	0	0	589	262	0	0	0	0	0	142	0	18	0	0	29	22	40
SP174	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Bacteroidaceae;Bacteroidaceae_[G-1];sp._oral_taxon_272	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	13	59	7	7	7
SP176	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptoniphilaceae;Parvimonas;micra	11	0	251	205	0	0	87	47	30	0	2	141	36	230	0	168	79	182	29	11
SP177	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Micrococcaceae;Rothia;dentocariosa	7425	0	28	77	881	0	861	579	0	0	10	0	0	0	3391	62	49	0	0	0
SP178	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;goodfellowii	567	0	158	219	0	5	51	0	7	0	0	0	0	0	0	0	0	4	0	0
SP179	Bacteria;Chloroflexi;Anaerolineae;Anaerolineales;Anaerolineaceae;Anaerolineae_[G-1];sp._oral_taxon_439	0	0	0	0	0	0	0	0	8	0	0	0	0	4	0	0	0	23	19	0
SP18	Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiales_[F-1];Clostridiales_[F-1][G-1];sp._oral_taxon_093	0	0	3	0	0	11	0	0	0	0	0	0	0	0	0	0	0	47	27	33
SP181	Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp._oral_taxon_513	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	42	38	147
SP182	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Anaeroglobus;geminatus	0	0	0	9	0	0	0	0	0	0	0	0	45	0	0	58	126	14	26	0
SP183	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_247	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	561	77	48
SP185	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._oral_taxon_212	57	7	215	48	0	141	0	0	0	0	0	0	0	0	17	0	0	24	20	24
SP186	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Dialister;sp._oral_taxon_119	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	18	17	4	0	0
SP187	Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;gracilis	56	0	234	137	60	43	28	278	35	0	84	102	10	50	3	448	69	241	38	14
SP188	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;intermedius	382	0	0	283	38	0	75	0	0	0	11	0	0	0	0	0	0	0	0	0
SP19	Bacteria;Firmicutes;Bacilli;Lactobacillales;Carnobacteriaceae;Granulicatella;elegans	0	0	0	0	0	0	0	0	0	0	0	0	0	24	0	0	0	0	7	0
SP190	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;tigurinus	0	0	0	0	176	11	0	68	0	0	0	0	0	0	0	0	0	0	22	0
SP191	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_231	0	0	0	0	0	11	7	0	14	0	0	92	80	63	0	0	0	51	7	0
SP192	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;marshii	0	0	0	0	0	0	0	0	0	0	0	0	8	0	0	0	0	17	18	0
SP193	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;umeaense	10	0	32	0	24	0	106	23	6	0	0	15	35	6	9	0	0	0	0	0
SP196	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-1];[Eubacterium]_infirmum	7	0	9	8	0	13	0	0	14	0	0	0	10	0	0	4	1	23	21	0
SP197	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Oribacterium;sp._oral_taxon_078	0	0	11	134	0	0	0	0	48	0	0	26	34	0	0	12	23	0	0	0
SP198	Bacteria;Synergistetes;Synergistia;Synergistales;Synergistaceae;Fretibacterium;fastidiosum	0	0	0	0	0	0	0	0	27	0	0	0	0	0	0	6	11	156	23	0
SP199	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;rava	0	0	7	0	0	10	0	44	0	0	0	0	7	0	0	0	0	0	0	7
SP2	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptococcaceae;Peptococcus;sp._oral_taxon_167	0	0	34	73	0	0	7	0	10	0	0	0	0	0	0	0	0	54	12	8
SP200	Bacteria;Proteobacteria;Betaproteobacteria;Burkholderiales;Burkholderiaceae;Lautropia;mirabilis	83	0	11	7	0	6	0	0	0	0	0	0	0	0	78	0	0	16	0	0
SP201	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcus;stomatis	0	0	29	20	0	10	0	49	68	0	6	0	8	26	0	0	0	11	82	36
SP204	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;mutans	0	0	0	0	7	0	7	0	0	0	0	0	0	0	6	0	0	0	0	0
SP205	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Stomatobaculum;longum	0	0	0	0	12	0	0	0	0	0	0	0	9	0	0	7	0	0	0	0
SP206	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sanguinis	530	0	31	65	10	14	142	70	0	0	66	20	0	121	373	0	0	89	0	0
SP208	Bacteria;Bacteroidetes;Bacteroidetes_[C-1];Bacteroidetes_[O-1];Bacteroidetes_[F-1];Bacteroidetes_[G-3];sp._oral_taxon_365	0	0	9	0	0	7	0	0	58	0	0	0	0	0	0	0	0	14	13	10
SP209	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Kingella;oralis	58	0	2	0	6	3	21	14	0	0	0	5	0	7	61	18	26	0	0	0
SP21	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;nucleatum_subsp._vincentii	82	0	252	475	143	427	856	1204	349	0	20	545	53	1073	0	1307	1143	310	547	95
SP210	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Stomatobaculum;sp._oral_taxon_373	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	12	4	5
SP212	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Veillonellaceae_[G-1];sp._oral_taxon_132	0	0	0	0	0	0	0	0	0	0	0	31	0	0	0	0	2	0	0	0
SP213	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;vestibularis	30	0	0	0	20	0	12	0	0	0	0	0	0	0	0	0	0	0	0	0
SP214	Bacteria;Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Ruminococcaceae_[G-2];sp._oral_taxon_085	0	0	54	0	0	0	0	16	8	0	0	2	17	0	0	0	0	0	6	0
SP215	Bacteria;Actinobacteria;Coriobacteriia;Coriobacteriales;Coriobacteriaceae;Atopobium;rimae	0	0	36	35	0	20	0	8	0	0	0	0	13	0	0	8	8	6	0	0
SP216	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;salivae	6	0	0	0	93	0	11	21	0	0	0	15	0	20	0	0	15	0	0	0
SP217	Bacteria;Firmicutes;Bacilli;Lactobacillales;Aerococcaceae;Abiotrophia;defectiva	30	0	17	0	0	0	0	0	0	0	10	0	14	15	0	0	0	0	0	0
SP218	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;naviforme	45	0	118	238	0	0	0	0	0	0	0	8	0	0	0	0	0	0	0	0
SP219	Bacteria;Proteobacteria;Deltaproteobacteria;Desulfovibrionales;Desulfomicrobiaceae;Desulfomicrobium;orale	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	115	0	7
SP22	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;dianae	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	39	37	0
SP220	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sp._oral_taxon_919	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	16	3	3
SP221	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;israelii	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	27	0	0
SP222	Bacteria;Proteobacteria;Deltaproteobacteria;Desulfobacterales;Desulfobulbaceae;Desulfobulbus;sp._oral_taxon_041	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	11	15	7	0
SP223	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Shuttleworthia;satelles	8	0	29	5	0	10	0	0	5	0	0	0	0	0	0	0	0	0	0	0
SP224	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp._oral_taxon_324	47	0	83	141	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
SP226	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;sp._oral_taxon_277	0	0	0	0	0	0	0	0	0	0	0	20	30	179	0	0	0	0	0	17
SP227	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Kingella;denitrificans	0	0	0	0	0	17	0	0	0	0	0	0	0	0	10	24	16	0	0	0
SP228	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter;sp._Oral_Taxon_C51	0	0	66	0	0	0	0	0	0	6	0	0	0	19	0	0	0	0	0	0
SP229	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;shahii	0	0	48	0	0	137	105	0	0	0	0	0	0	0	27	0	0	0	0	0
SP23	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;australis	13	0	9	0	0	0	0	0	0	0	183	0	0	0	0	0	0	0	0	10
SP230	Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp._oral_taxon_512	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	11	3	0	0	13
SP231	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;saccharolytica	0	0	31	0	0	19	0	0	10	0	0	0	0	0	0	0	0	30	39	0
SP232	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Catonella;sp._oral_taxon_451	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	73	13	9
SP233	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Johnsonella;ignava	3	0	25	0	0	0	0	0	11	0	6	0	0	0	0	0	0	29	0	0
SP234	Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;sp._oral_taxon_044	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	402	8
SP235	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Micrococcaceae;Rothia;aeria	506	0	5	15	0	0	56	0	0	0	0	0	0	0	229	116	22	30	0	0
SP237	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;micans	0	0	82	0	0	6	0	0	0	0	0	0	0	0	0	0	0	65	222	0
SP238	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp._oral_taxon_475	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	58	0
SP239	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;pharyngis	0	0	0	0	0	16	0	0	0	0	0	0	0	3	0	0	0	0	0	0
SP24	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Dialister;pneumosintes	0	0	37	7	0	10	0	28	10	0	0	7	8	16	0	31	50	5	13	4
SP240	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnospiraceae_[G-8];sp._oral_taxon_500	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	14	100	15	9
SP241	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-2];TM7_[G-5];sp._oral_taxon_356	0	0	270	0	0	242	4	620	294	0	13	51	83	23	0	0	0	0	91	0
SP243	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;infelix	0	0	20	0	0	0	0	0	7	0	0	0	14	0	0	0	0	0	6	0
SP246	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;wadei	18	0	148	0	112	0	30	244	62	0	0	169	81	197	63	29	0	0	0	0
SP247	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-1];sp._oral_taxon_347	1186	0	0	0	0	0	130	0	0	0	0	0	0	0	1399	0	0	0	0	0
SP249	Bacteria;Proteobacteria;Gammaproteobacteria;Cardiobacteriales;Cardiobacteriaceae;Cardiobacterium;hominis	0	0	5	0	2	0	9	0	0	0	0	0	0	0	8	8	0	0	0	0
SP25	Bacteria;Actinobacteria;Actinobacteria;Corynebacteriales;Corynebacteriaceae;Corynebacterium;matruchotii	200	3	54	28	6	4	27	0	11	0	0	13	14	40	616	283	559	68	0	0
SP252	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;elongata	0	0	13	0	0	17	0	0	0	0	0	0	0	0	0	8	0	6	4	6
SP253	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._oral_taxon_215	54	0	40	12	5	26	0	0	0	0	18	0	178	0	0	0	0	42	0	0
SP254	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sp._oral_taxon_137	0	0	0	0	0	13	0	0	0	0	0	5	0	0	0	0	0	0	0	0
SP255	Bacteria;Proteobacteria;Gammaproteobacteria;Cardiobacteriales;Cardiobacteriaceae;Cardiobacterium;valvarum	0	0	10	0	0	0	0	0	0	0	0	0	0	0	0	0	0	18	0	0
SP256	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;oris	12	0	0	0	6	0	0	0	0	0	0	0	0	0	27	0	0	0	0	0
SP258	Bacteria;Firmicutes;Mollicutes;Mycoplasmatales;Mycoplasmataceae;Mycoplasma;salivarium	0	0	8	13	0	0	0	4	0	0	0	0	42	0	0	10	39	0	0	0
SP259	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;multiformis	6	0	30	0	0	0	0	0	0	0	0	1	0	177	0	0	0	0	0	0
SP26	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;melaninogenica	118	0	0	11	26	22	123	32	0	0	4	32	126	556	0	0	0	17	0	0
SP260	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Veillonellaceae_[G-1];sp._oral_taxon_145	0	0	0	0	0	0	0	0	0	0	0	20	40	0	0	0	0	0	0	0
SP261	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp._oral_taxon_864	0	0	3	0	0	0	0	0	27	0	0	0	0	0	0	0	0	155	37	9
SP262	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_234	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	138	0	20
SP263	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Megasphaera;sp._oral_taxon_123	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	53	82	15	12	0
SP264	Bacteria;Proteobacteria;Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae;Paracoccus;sp._Oral_Taxon_H67	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	21	0	0
SP267	Bacteria;Firmicutes;Bacilli;Bacillales;Gemellaceae;Gemella;bergeri	0	0	0	0	7	0	58	18	0	0	0	0	0	0	0	0	0	0	0	0
SP268	Bacteria;SR1;SR1_[C-1];SR1_[O-1];SR1_[F-1];SR1_[G-1];sp._oral_taxon_874	0	0	0	0	0	88	30	0	0	0	3	0	0	0	5	0	0	0	12	0
SP27	Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;segnis	0	0	8	0	0	132	0	0	0	0	0	0	0	0	0	0	12	0	0	0
SP270	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-9];[Eubacterium]_brachy	0	0	11	0	2	10	0	0	4	0	0	0	28	0	0	28	10	120	10	0
SP271	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Veillonella;atypica	20	0	0	0	24	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
SP272	Bacteria;Proteobacteria;Alphaproteobacteria;Sphingomonadales;Sphingomonadaceae;Sphingomonas;hankookensis	0	0	21	4	0	14	0	0	0	0	0	0	6	0	0	0	0	0	0	0
SP274	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter;lwoffii	0	0	0	0	0	0	0	0	14	0	0	0	29	0	0	0	0	0	0	0
SP275	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptoniphilaceae;Parvimonas;sp._oral_taxon_393	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	36	0
SP276	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp._oral_taxon_380	0	0	0	0	11	0	0	35	12	0	3	36	8	38	7	0	0	0	0	0
SP277	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-7];[Eubacterium]_yurii_subsp._yurii_&_margaretiae	0	0	36	0	0	0	0	0	0	0	0	0	0	0	0	0	0	137	12	5
SP278	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;flueggei	0	0	0	0	0	4	0	0	0	0	0	0	16	0	0	0	0	0	0	0
SP28	Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Haemophilus;parainfluenzae	482	0	32	0	14	31	110	30	0	0	1032	0	37	0	53	0	0	12	11	20
SP280	Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;actinomycetemcomitans	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	122	74	14
SP282	Bacteria;Firmicutes;Mollicutes;Mycoplasmatales;Mycoplasmataceae;Mycoplasma;faucium	0	0	0	0	0	0	0	0	0	0	0	0	0	10	0	0	0	29	26	32
SP283	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-6];[Eubacterium]_nodatum	0	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	16	0	2
SP284	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Bergeyella;sp._oral_taxon_900	0	0	32	0	0	8	49	0	0	0	0	0	0	0	0	0	0	7	9	9
SP285	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;histicola	46	0	0	5	0	0	0	0	0	0	0	0	0	27	0	0	0	0	0	0
SP286	Bacteria;Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Erysipelotrichaceae_[G-1];sp._oral_taxon_905	0	0	17	7	0	0	0	0	15	0	0	0	22	0	0	5	0	0	3	0
SP289	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-5];[Eubacterium]_saphenum	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	11	10	12
SP29	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;catoniae	0	0	25	0	0	18	426	0	0	0	0	0	0	0	0	9	0	64	11	16
SP290	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnospiraceae_[G-2];sp._oral_taxon_088	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	72	7	0
SP291	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter;sp._str._DR1	0	0	232	0	0	470	0	0	0	54	0	34	0	156	0	0	0	0	0	0
SP294	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;dentalis	0	0	0	0	0	0	0	0	7	0	0	0	0	15	0	0	0	0	0	0
SP295	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;odontolyticus	0	0	0	0	0	0	0	0	0	0	0	0	0	12	0	6	10	0	0	0
SP296	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Empedobacter;falsenii	0	10	0	32	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
SP3	Bacteria;Proteobacteria;Betaproteobacteria;Burkholderiales;Comamonadaceae;Delftia;sp._Oral_Taxon_A59	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	20	0	0
SP30	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp._oral_taxon_056	0	0	0	0	0	108	1	0	0	0	0	0	0	0	0	0	0	0	0	0
SP300	Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-4];sp._oral_taxon_369	0	0	0	0	0	5	0	0	0	0	0	0	9	3	0	2	11	111	22	48
SP301	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sp._oral_taxon_479	0	0	0	0	0	0	0	5	0	0	0	0	5	0	0	0	0	5	0	8
SP304	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;trevisanii	0	0	0	0	0	0	103	30	0	0	0	0	0	0	0	0	0	84	0	0
SP305	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;sp._oral_taxon_171	18	0	0	0	0	0	0	0	0	0	0	0	0	9	25	0	0	0	0	0
SP307	Bacteria;Proteobacteria;Alphaproteobacteria;Rhizobiales;Rhizobiaceae;Rhizobium;larrymoorei_Oral_Taxon_D45	0	0	63	0	0	7	0	0	0	0	0	11	0	36	0	0	0	0	0	0
SP309	Bacteria;Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Solobacterium;moorei	0	0	45	14	0	0	0	19	5	0	0	0	25	12	0	11	0	2	0	0
SP31	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;nucleatum_subsp._animalis	871	13	989	3389	612	167	74	854	885	0	22	1141	326	106	0	244	294	143	169	68
SP310	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_262	0	0	0	0	0	0	6	0	0	0	0	0	0	0	0	0	0	76	15	0
SP311	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Oribacterium;sinus	11	0	0	0	0	0	0	0	0	0	7	0	0	0	0	0	0	8	4	0
SP312	Bacteria;Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Bulleidia;extructa	0	0	7	0	0	0	0	0	0	0	0	0	0	53	0	0	0	0	0	0
SP314	Bacteria;Proteobacteria;Alphaproteobacteria;Caulobacterales;Caulobacteraceae;Brevundimonas;vesicularis_Oral_Taxon_C59	0	0	21	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
SP315	Bacteria;Proteobacteria;Gammaproteobacteria;Chromatiales;Chromatiaceae;Rheinheimera;chironomi	0	0	7	0	0	0	0	0	0	0	0	0	7	8	0	0	0	0	0	0
SP317	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Veillonellaceae_[G-1];sp._oral_taxon_155	0	0	0	0	0	0	0	0	0	0	0	18	8	0	0	0	0	0	0	0
SP32	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sputigena	19	0	0	0	0	12	97	6	0	0	0	0	7	0	0	0	0	0	4	0
SP320	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;sp._oral_taxon_083	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	37	0
SP321	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-6];sp._oral_taxon_870	0	0	41	0	0	0	10	80	0	0	0	0	29	0	0	0	0	0	0	0
SP322	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter;baumannii	0	0	0	0	0	0	0	0	0	0	0	0	19	37	0	0	0	0	0	0
SP323	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Micrococcaceae;Micrococcus;luteus_Oral_Taxon_C78	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	20	0	0
SP325	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;flava	0	0	0	0	0	0	0	0	0	0	23	0	0	0	0	0	0	0	0	0
SP327	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._oral_taxon_221	7	0	9	0	0	0	23	0	0	0	0	0	0	0	0	0	0	0	0	0
SP329	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sp._oral_taxon_146	0	0	0	0	0	0	0	21	0	0	0	0	0	0	0	0	0	0	0	0
SP33	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._oral_taxon_392	0	0	67	0	0	97	35	0	20	0	0	121	496	76	13	0	0	69	33	0
SP330	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;naeslundii	78	0	0	0	0	0	0	0	0	0	0	0	0	5	47	0	0	8	0	0
SP335	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_238	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	347	59	72
SP336	Bacteria;Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Erysipelotrichaceae_[G-1];sp._oral_taxon_904	0	0	0	0	0	0	0	0	37	0	0	0	0	0	0	0	0	0	0	0
SP337	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_258	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	26	35	14
SP339	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp._oral_taxon_301	0	0	0	0	0	0	0	5	0	0	0	0	4	0	0	7	10	0	0	0
SP34	Bacteria;Proteobacteria;Alphaproteobacteria;Caulobacterales;Caulobacteraceae;Asticcacaulis;excentricus	0	0	8	0	0	0	0	0	0	0	0	0	0	14	0	0	0	0	0	0
SP341	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;baroniae	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	5	6	65	36	0
SP342	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_270	0	0	0	0	0	0	0	0	0	0	0	2	4	11	0	0	0	7	3	0
SP343	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._oral_taxon_223	0	0	0	0	58	0	9	9	53	0	0	0	0	0	0	0	0	0	0	0
SP344	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;massiliensis	32	0	0	0	0	0	0	0	0	0	0	0	0	0	12	0	0	0	0	0
SP345	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sp._Oral_Taxon_G55	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	6	18	0
SP346	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter;sp._Oral_Taxon_C81	0	0	0	0	0	0	0	0	0	0	0	36	0	78	0	0	0	0	0	0
SP348	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;mucosa	0	0	0	0	0	0	0	0	0	0	0	0	11	0	0	0	0	19	0	0
SP35	Bacteria;Proteobacteria;Alphaproteobacteria;Caulobacterales;Caulobacteraceae;Caulobacter;crescentus	0	0	0	0	0	5	0	0	0	0	0	8	0	14	0	0	0	0	0	0
SP350	Bacteria;Bacteroidetes;Bacteroidetes_[C-1];Bacteroidetes_[O-1];Bacteroidetes_[F-1];Bacteroidetes_[G-3];sp._oral_taxon_280	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	47	29	13
SP351	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;sp._oral_taxon_525	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	20	0	0	0	0
SP352	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_517	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	27	0	0
SP353	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;sp._oral_taxon_951	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	26	27	25
SP36	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;dentisani	47	0	350	14	32	69	322	24	0	0	0	15	129	91	253	330	142	0	4	55
SP37	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sputigena	0	0	0	0	3	0	0	25	0	0	0	8	4	0	0	6	0	82	69	0
SP38	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;nucleatum_subsp._polymorphum	0	0	13	0	20	82	116	0	0	0	0	153	601	191	44	25	54	230	116	42
SP39	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp._oral_taxon_335	0	0	0	0	0	6	0	13	3	0	0	30	0	26	9	0	6	0	4	4
SP4	Bacteria;Spirochaetes;Spirochaetes;Spirochaetales;Spirochaetaceae;Treponema;sp._Oral_Taxon_G77	0	0	0	0	0	0	0	0	0	0	0	0	9	9	0	0	0	9	0	0
SP40	Bacteria;Proteobacteria;Betaproteobacteria;Burkholderiales;Comamonadaceae;Delftia;acidovorans	0	0	10	0	0	8	0	0	0	0	0	3	0	24	0	0	0	0	0	0
SP42	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;tannerae	16	0	155	310	4	141	74	464	188	0	0	4	114	70	0	368	181	207	648	20
SP43	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Moraxella;osloensis	0	0	7	0	0	0	0	0	0	0	0	0	73	30	0	5	0	62	0	0
SP44	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter;sp._Oral_Taxon_A58	0	0	0	74	0	8	0	0	0	5	0	8	0	31	0	9	0	278	0	0
SP45	Bacteria;Firmicutes;Bacilli;Lactobacillales;Carnobacteriaceae;Granulicatella;adiacens	93	0	16	12	24	8	24	66	1	0	61	7	7	52	78	103	169	18	0	6
SP46	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sp._oral_taxon_892	0	0	0	0	0	0	0	0	0	0	0	0	6	0	0	0	0	25	8	0
SP47	Bacteria;Synergistetes;Synergistia;Synergistales;Synergistaceae;Fretibacterium;sp._oral_taxon_360	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	55	63	168	0	0
SP48	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;sp._oral_taxon_180	0	0	0	0	0	0	0	0	0	0	0	11	8	19	3	0	0	0	0	0
SP49	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;denticola	0	0	60	41	0	50	3	11	0	0	0	0	1250	70	0	78	28	0	0	0
SP50	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;sp._oral_taxon_481	0	0	0	0	0	0	0	16	0	0	0	7	0	0	0	0	0	5	0	0
SP51	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnospiraceae_[G-3];sp._oral_taxon_100	4	0	50	4	0	46	5	4	46	0	0	10	135	19	0	0	0	42	20	9
SP52	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;granulosa	0	0	333	54	21	87	271	0	10	0	0	45	34	143	26	5	4	0	0	0
SP53	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;parasanguinis_II	167	0	9	4	139	0	85	39	0	0	26	0	6	47	11	0	0	0	0	0
SP54	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;gordonii	33	0	0	0	37	46	64	18	0	0	0	0	96	26	60	71	321	77	0	0
SP55	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;lecithinolyticum	0	0	7	0	0	0	0	0	7	0	0	14	23	8	0	0	0	114	8	0
SP56	Bacteria;Firmicutes;Bacilli;Bacillales;Gemellaceae;Gemella;haemolysans	118	0	4	0	0	0	20	0	0	0	10	0	0	9	7	0	0	0	6	0
SP57	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Dialister;invisus	61	3	226	156	31	22	4	66	85	0	0	4	52	12	0	48	55	14	30	12
SP59	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;hongkongensis	0	0	35	70	0	0	0	0	0	0	0	69	0	109	744	282	80	0	0	0
SP6	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Veillonella;parvula_group	1162	0	244	1060	629	61	1093	2213	0	0	195	39	21	196	255	73	290	377	210	0
SP60	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;cristatus	0	0	154	0	0	8	0	0	21	0	8	116	91	1370	309	58	81	9	0	0
SP61	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;sp._oral_taxon_808	0	0	18	42	0	0	0	5	40	0	0	0	95	0	0	0	12	0	0	0
SP62	Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;sp._oral_taxon_169	437	0	0	0	19	0	44	3	0	0	0	0	22	38	190	0	0	0	0	0
SP63	Bacteria;Actinobacteria;Coriobacteriia;Coriobacteriales;Coriobacteriaceae;Atopobium;parvulum	20	0	0	0	33	0	3	0	0	0	0	0	0	0	0	0	0	0	10	0
SP65	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;sp._oral_taxon_473	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	337	42
SP66	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;sp._oral_taxon_279	11	0	57	26	0	100	0	0	0	0	0	0	0	0	31	9	0	11	38	0
SP67	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;endodontalis	8	0	66	210	0	154	46	21	428	0	0	167	363	92	0	0	0	11563	1413	1355
SP68	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._oral_taxon_417	14	0	8	73	22	28	58	0	0	0	0	0	0	0	0	0	0	0	0	0
SP69	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Bacteroidales_[F-2];Bacteroidales_[G-2];sp._oral_taxon_274	0	0	17	0	8	73	0	20	39	0	4	0	4	0	0	294	200	704	103	37
SP7	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-1];sp._oral_taxon_348	65	3	102	21	0	105	0	0	46	0	0	0	0	0	0	64	37	44	18	16
SP72	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;sp._oral_taxon_275	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	47	123	31
SP73	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp._oral_taxon_423	105	0	50	136	667	188	1361	2047	0	0	205	0	0	0	249	47	68	18	0	17
SP74	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Catonella;morbi	0	0	0	6	0	11	2	32	24	0	0	35	0	23	0	10	0	182	154	15
SP76	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;anginosus	0	0	0	0	0	0	0	217	6	0	0	17	35	23	0	0	0	0	0	0
SP77	Bacteria;Actinobacteria;Actinobacteria;Propionibacteriales;Propionibacteriaceae;Propionibacterium;propionicum	315	0	0	0	0	0	2	0	0	0	7	0	0	0	10	10	0	16	0	0
SP78	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Selenomonas;noxia	7	0	43	10	9	17	0	6	17	0	0	22	25	27	0	9	9	13	0	0
SP79	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Butyrivibrio;sp._oral_taxon_080	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	46	39	0
SP8	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;vincentii	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	23	0
SP80	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-3];sp._oral_taxon_351	0	0	15	16	9	7	0	12	35	0	0	0	25	0	0	0	0	0	0	3
SP82	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._oral_taxon_225	0	0	0	0	0	31	0	0	0	0	0	0	0	0	4	0	0	6	3	7
SP83	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._Oral_Taxon_B57	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	24	40	26
SP84	Bacteria;Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Eggerthia;catenaformis	0	0	0	0	0	0	0	0	12	0	0	0	0	20	0	0	0	5	0	4
SP85	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-1];sp._oral_taxon_346	15	0	416	21	102	159	0	125	364	0	0	8	59	30	0	115	45	33	217	28
SP86	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;saburreum	40	0	131	31	0	33	14	202	7	0	0	20	41	49	0	25	9	0	0	0
SP87	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp._oral_taxon_070	3	0	80	0	197	6	18	74	0	0	0	0	177	0	0	0	4	0	16	0
SP88	Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;sicca	22	0	16	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	34	6
SP89	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;hofstadii	113	5	221	193	0	19	45	0	0	0	0	0	43	0	203	0	0	0	0	27
SP9	Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Johnsonella;sp._oral_taxon_166	0	0	0	0	0	0	0	0	27	0	0	0	0	0	0	0	0	34	0	27
SP90	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp._oral_taxon_314	0	0	0	0	0	83	0	393	0	0	0	20	37	79	0	0	0	0	0	0
SP91	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp._oral_taxon_498	0	0	0	0	8	26	0	29	0	0	0	0	0	0	0	0	0	20	550	15
SP92	Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Treponema;denticola	0	0	8	0	0	24	5	0	50	0	0	18	27	86	0	0	0	312	120	302
SP93	Bacteria;Bacteroidetes;Bacteroidetes_[C-1];Bacteroidetes_[O-1];Bacteroidetes_[F-1];Bacteroidetes_[G-5];sp._oral_taxon_511	0	0	62	0	0	51	0	0	67	0	0	0	0	0	0	0	0	25	175	9
SP95	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp._oral_taxon_064	92	0	62	48	0	82	98	39	0	0	0	0	0	0	244	0	0	0	13	13
SP97	Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter;sp._Oral_Taxon_C99	0	0	342	0	0	188	0	0	0	39	0	30	0	156	0	0	0	0	0	0
SP98	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;sp._HOT_204	11	0	28	68	0	0	26	0	0	0	0	21	0	28	0	0	0	254	87	25
SP99	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;maculosa	0	0	57	6	15	19	0	212	0	0	0	64	23	27	0	13	1	24	19	0
SPN1	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;nucleatum_subsp._animalis_nov_97.859%	0	0	0	0	0	0	110	191	18	0	0	0	0	0	0	558	215	0	0	0
SPN2	Bacteria;Proteobacteria;Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae;Gemmobacter;aquatilis_nov_97.921%	0	0	16	0	7	0	0	3	0	0	0	0	0	0	0	20	0	229	0	0
SPN3	Bacteria;Bacteroidetes;Bacteroidetes_[C-1];Bacteroidetes_[O-1];Bacteroidetes_[F-1];Bacteroidetes_[G-5];sp._oral_taxon_505_nov_95.652%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	92	55	101
SPN4	Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp._oral_taxon_903_nov_97.505%	43	0	71	113	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
SPN5	Bacteria;Saccharibacteria_(TM7);TM7_[C-1];TM7_[O-1];TM7_[F-1];TM7_[G-1];sp._oral_taxon_869_nov_95.585%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	73	44	0
SPP1	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;multispecies_spp1_2	0	0	0	0	0	0	0	0	0	0	0	0	0	61	0	0	0	0	0	3
SPP4	Bacteria;Proteobacteria;Alphaproteobacteria;Rhizobiales;Rhizobiales_multifamily;Rhizobiales_multifamily_multigenus;multispecies_spp4_2	0	0	0	0	0	0	0	0	0	0	0	0	0	54	0	0	0	0	0	0
SPP5	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;multispecies_spp5_2	0	0	0	0	0	0	0	29	0	0	0	64	21	25	0	0	0	0	0	0
SPP6	Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;multispecies_spp6_2	384	0	7	13	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
SPP7	Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Fusobacteriaceae;Fusobacterium;multispecies_spp7_2	49	0	116	237	0	0	0	0	0	0	0	161	0	0	0	0	0	0	0	0
SPP9	Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Veillonella;multispecies_spp9_2	32	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Download OTU Tables at Different Taxonomy Levels
Phylum	Count*:	Relative**:	CLR***:
Class	Count*:	Relative**:	CLR***:
Order	Count*:	Relative**:	CLR***:
Family	Count*:	Relative**:	CLR***:
Genus	Count*:	Relative**:	CLR***:
Species	Count*:	Relative**:	CLR***:
* Read count
** Relative abundance (count/total sample count)
*** Centered log ratio transformed abundance

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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.

Taxonomy Bar Plots for All Samples

Taxonomy Bar Plots for Individual Comparison Groups

Comparison No.	Comparison Name	Families		Genera		Species
Comparison 1	DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118	PDF	SVG	PDF	SVG	PDF	SVG

VIII. Analysis - Alpha Diversity

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).

References:

Alpha Diversity Analysis by Rarefaction

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].

References:

Willis AD. Rarefaction, Alpha Diversity, and Statistics. Front Microbiol. 2019 Oct 23;10:2407. doi: 10.3389/fmicb.2019.02407. PMID: 31708888; PMCID: PMC6819366.

Boxplot of Alpha-diversity Indices

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

Comparison 1

DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118

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The above comparisons are at the species-level. Comparisons of other taxonomy levels, from phylum to genus, are also available:

IX. Analysis - Beta Diversity

NMDS and PCoA Plots

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.

References:

Plantinga, AM, Wu, MC (2021). Beta Diversity and Distance-Based Analysis of Microbiome Data. In: Datta, S., Guha, S. (eds) Statistical Analysis of Microbiome Data. Frontiers in Probability and the Statistical Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-73351-3_5

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

Comparison No.	Comparison Name	NMDA				PCoA
Comparison No.	Comparison Name	Bray-Curtis		CLR Euclidean		Bray-Curtis		CLR Euclidean
Comparison 1	DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118	PDF	SVG	PDF	SVG	PDF	SVG	PDF	SVG

Interactive 3D PCoA Plots - Bray-Curtis Dissimilarity

Interactive 3D PCoA Plots - Euclidean Distance

Interactive 3D PCoA Plots - Correlation Coefficients

X. Analysis - Differential Abundance

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.

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.

ANCOM Differential Abundance Analysis

ANCOM Results for Individual Comparisons

Comparison No.	Comparison Name
Comparison 1.	DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118

ANCOM-BC2 Differential Abundance Analysis

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:

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.

ANCOM-BC Results for Individual Comparisons

Comparison No.	Comparison Name
Comparison 1.	DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118

LEfSe - Linear Discriminant Analysis Effect Size

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.

DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118

XI. Analysis - Heatmap Profile

Species vs Sample Abundance Heatmap for All Samples

Heatmaps for Individual Comparisons

A) Two-way clustering - clustered on both columns (Samples) and rows (organism)

Comparison No.	Comparison Name	Family Level		Genus Level		Species Level
Comparison 1	DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118	PDF	SVG	PDF	SVG	PDF	SVG

B) One-way clustering - clustered on rows (organism) only

Comparison No.	Comparison Name	Family Level		Genus Level		Species Level
Comparison 1	DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118	PDF	SVG	PDF	SVG	PDF	SVG

C) No clustering

Comparison No.	Comparison Name	Family Level		Genus Level		Species Level
Comparison 1	DGP103 vs DGP106 vs DGP107 vs DGP108 vs DGP116 vs DGP118	PDF	SVG	PDF	SVG	PDF	SVG

XII. Analysis - Network Association

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.

References:

Friedman J, Alm EJ. Inferring correlation networks from genomic survey data. PLoS Comput Biol. 2012;8(9):e1002687. doi: 10.1371/journal.pcbi.1002687. Epub 2012 Sep 20. PMID: 23028285; PMCID: PMC3447976.

Association Network Inference by SparCC

XIII. Disclaimer

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.