Project FOMC4468_V1V3 services include NGS sequencing of the V1V3 region of the 16S rRNA amplicons from the samples. First and foremost, please
download this report, as well as the sequence raw data from the download links provided below.
These links will expire after 60 days. We cannot guarantee the availability of your data after 60 days.
Full Bioinformatics analysis service was requested. We provide many analyses, starting from the raw sequence quality and noise filtering, pair reads merging, as well as chimera filtering for the sequences, using the
DADA2 denosing algorithm and pipeline.
We also provide many downstream analyses such as taxonomy assignment, alpha and beta diversity analyses, and differential abundance analysis.
For taxonomy assignment, most informative would be the taxonomy barplots. We provide an interactive barplots to show the relative abundance of microbes at different taxonomy levels (from Phylum to species) that you can choose.
If you specify which groups of samples you want to compare for differential abundance, we provide both ANCOM and LEfSe differential abundance analysis.
The samples were processed and analyzed with the ZymoBIOMICS® Service: Targeted
Metagenomic Sequencing (Zymo Research, Irvine, CA).
DNA Extraction: If DNA extraction was performed, one of three different DNA
extraction kits was used depending on the sample type and sample volume and were
used according to the manufacturer’s instructions, unless otherwise stated. The kit used
in this project is marked below:
☐
ZymoBIOMICS® DNA Miniprep Kit (Zymo Research, Irvine, CA)
☐
ZymoBIOMICS® DNA Microprep Kit (Zymo Research, Irvine, CA)
☐
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)
☐
Other: NA
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® MiSeq™ with a V3 reagent kit
(600 cycles). The sequencing was performed with 10% PhiX spike-in.
The complete report of your project, including all links in this report, can be downloaded by clicking the link provided below. The downloaded file is a compressed ZIP file and once unzipped, open the file “REPORT.html” (may only shown as "REPORT" in your computer) by double clicking it. Your default web browser will open it and you will see the exact content of this report.
Please download and save the file to your computer storage device. The download link will expire after 60 days upon your receiving of this report.
Complete report download link:
To view the report, please follow the following steps:
1.
Download the .zip file from the report link above.
2.
Extract all the contents of the downloaded .zip file to your desktop.
3.
Open the extracted folder and find the "REPORT.html" (may shown as only "REPORT").
4.
Open (double-clicking) the REPORT.html file. Your default browser will open the top age of the complete report. Within the
report, there are links to view all the analyses performed for the project.
The raw NGS sequence data is available for download with the link provided below. The data is a compressed ZIP file and can be unzipped to individual sequence files.
Since this is a pair-end sequencing, each of your samples is represented by two sequence files, one for READ 1,
with the file extension “*_R1.fastq.gz”, another READ 2, with the file extension “*_R1.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 R1 and R2 fastq files are listed in the table below:
Sample ID
Read 1 File Name
Read 2 File Name
S100
zr4468_100V1V3_R1.fastq.gz
zr4468_100V1V3_R2.fastq.gz
S101
zr4468_101V1V3_R1.fastq.gz
zr4468_101V1V3_R2.fastq.gz
S102
zr4468_102V1V3_R1.fastq.gz
zr4468_102V1V3_R2.fastq.gz
S103
zr4468_103V1V3_R1.fastq.gz
zr4468_103V1V3_R2.fastq.gz
S104
zr4468_104V1V3_R1.fastq.gz
zr4468_104V1V3_R2.fastq.gz
S105
zr4468_105V1V3_R1.fastq.gz
zr4468_105V1V3_R2.fastq.gz
S106
zr4468_106V1V3_R1.fastq.gz
zr4468_106V1V3_R2.fastq.gz
S107
zr4468_107V1V3_R1.fastq.gz
zr4468_107V1V3_R2.fastq.gz
S108
zr4468_108V1V3_R1.fastq.gz
zr4468_108V1V3_R2.fastq.gz
S109
zr4468_109V1V3_R1.fastq.gz
zr4468_109V1V3_R2.fastq.gz
S010
zr4468_10V1V3_R1.fastq.gz
zr4468_10V1V3_R2.fastq.gz
S110
zr4468_110V1V3_R1.fastq.gz
zr4468_110V1V3_R2.fastq.gz
S111
zr4468_111V1V3_R1.fastq.gz
zr4468_111V1V3_R2.fastq.gz
S112
zr4468_112V1V3_R1.fastq.gz
zr4468_112V1V3_R2.fastq.gz
S113
zr4468_113V1V3_R1.fastq.gz
zr4468_113V1V3_R2.fastq.gz
S114
zr4468_114V1V3_R1.fastq.gz
zr4468_114V1V3_R2.fastq.gz
S115
zr4468_115V1V3_R1.fastq.gz
zr4468_115V1V3_R2.fastq.gz
S116
zr4468_116V1V3_R1.fastq.gz
zr4468_116V1V3_R2.fastq.gz
S117
zr4468_117V1V3_R1.fastq.gz
zr4468_117V1V3_R2.fastq.gz
S118
zr4468_118V1V3_R1.fastq.gz
zr4468_118V1V3_R2.fastq.gz
S119
zr4468_119V1V3_R1.fastq.gz
zr4468_119V1V3_R2.fastq.gz
S011
zr4468_11V1V3_R1.fastq.gz
zr4468_11V1V3_R2.fastq.gz
S120
zr4468_120V1V3_R1.fastq.gz
zr4468_120V1V3_R2.fastq.gz
S121
zr4468_121V1V3_R1.fastq.gz
zr4468_121V1V3_R2.fastq.gz
S122
zr4468_122V1V3_R1.fastq.gz
zr4468_122V1V3_R2.fastq.gz
S123
zr4468_123V1V3_R1.fastq.gz
zr4468_123V1V3_R2.fastq.gz
S124
zr4468_124V1V3_R1.fastq.gz
zr4468_124V1V3_R2.fastq.gz
S125
zr4468_125V1V3_R1.fastq.gz
zr4468_125V1V3_R2.fastq.gz
S126
zr4468_126V1V3_R1.fastq.gz
zr4468_126V1V3_R2.fastq.gz
S127
zr4468_127V1V3_R1.fastq.gz
zr4468_127V1V3_R2.fastq.gz
S128
zr4468_128V1V3_R1.fastq.gz
zr4468_128V1V3_R2.fastq.gz
S129
zr4468_129V1V3_R1.fastq.gz
zr4468_129V1V3_R2.fastq.gz
S012
zr4468_12V1V3_R1.fastq.gz
zr4468_12V1V3_R2.fastq.gz
S130
zr4468_130V1V3_R1.fastq.gz
zr4468_130V1V3_R2.fastq.gz
S131
zr4468_131V1V3_R1.fastq.gz
zr4468_131V1V3_R2.fastq.gz
S132
zr4468_132V1V3_R1.fastq.gz
zr4468_132V1V3_R2.fastq.gz
S133
zr4468_133V1V3_R1.fastq.gz
zr4468_133V1V3_R2.fastq.gz
S134
zr4468_134V1V3_R1.fastq.gz
zr4468_134V1V3_R2.fastq.gz
S135
zr4468_135V1V3_R1.fastq.gz
zr4468_135V1V3_R2.fastq.gz
S136
zr4468_136V1V3_R1.fastq.gz
zr4468_136V1V3_R2.fastq.gz
S137
zr4468_137V1V3_R1.fastq.gz
zr4468_137V1V3_R2.fastq.gz
S138
zr4468_138V1V3_R1.fastq.gz
zr4468_138V1V3_R2.fastq.gz
S139
zr4468_139V1V3_R1.fastq.gz
zr4468_139V1V3_R2.fastq.gz
S013
zr4468_13V1V3_R1.fastq.gz
zr4468_13V1V3_R2.fastq.gz
S140
zr4468_140V1V3_R1.fastq.gz
zr4468_140V1V3_R2.fastq.gz
S141
zr4468_141V1V3_R1.fastq.gz
zr4468_141V1V3_R2.fastq.gz
S142
zr4468_142V1V3_R1.fastq.gz
zr4468_142V1V3_R2.fastq.gz
S143
zr4468_143V1V3_R1.fastq.gz
zr4468_143V1V3_R2.fastq.gz
S144
zr4468_144V1V3_R1.fastq.gz
zr4468_144V1V3_R2.fastq.gz
S145
zr4468_145V1V3_R1.fastq.gz
zr4468_145V1V3_R2.fastq.gz
S146
zr4468_146V1V3_R1.fastq.gz
zr4468_146V1V3_R2.fastq.gz
S147
zr4468_147V1V3_R1.fastq.gz
zr4468_147V1V3_R2.fastq.gz
S148
zr4468_148V1V3_R1.fastq.gz
zr4468_148V1V3_R2.fastq.gz
S149
zr4468_149V1V3_R1.fastq.gz
zr4468_149V1V3_R2.fastq.gz
S014
zr4468_14V1V3_R1.fastq.gz
zr4468_14V1V3_R2.fastq.gz
S150
zr4468_150V1V3_R1.fastq.gz
zr4468_150V1V3_R2.fastq.gz
S151
zr4468_151V1V3_R1.fastq.gz
zr4468_151V1V3_R2.fastq.gz
S152
zr4468_152V1V3_R1.fastq.gz
zr4468_152V1V3_R2.fastq.gz
S153
zr4468_153V1V3_R1.fastq.gz
zr4468_153V1V3_R2.fastq.gz
S154
zr4468_154V1V3_R1.fastq.gz
zr4468_154V1V3_R2.fastq.gz
S155
zr4468_155V1V3_R1.fastq.gz
zr4468_155V1V3_R2.fastq.gz
S156
zr4468_156V1V3_R1.fastq.gz
zr4468_156V1V3_R2.fastq.gz
S157
zr4468_157V1V3_R1.fastq.gz
zr4468_157V1V3_R2.fastq.gz
S158
zr4468_158V1V3_R1.fastq.gz
zr4468_158V1V3_R2.fastq.gz
S159
zr4468_159V1V3_R1.fastq.gz
zr4468_159V1V3_R2.fastq.gz
S015
zr4468_15V1V3_R1.fastq.gz
zr4468_15V1V3_R2.fastq.gz
S160
zr4468_160V1V3_R1.fastq.gz
zr4468_160V1V3_R2.fastq.gz
S161
zr4468_161V1V3_R1.fastq.gz
zr4468_161V1V3_R2.fastq.gz
S162
zr4468_162V1V3_R1.fastq.gz
zr4468_162V1V3_R2.fastq.gz
S163
zr4468_163V1V3_R1.fastq.gz
zr4468_163V1V3_R2.fastq.gz
S164
zr4468_164V1V3_R1.fastq.gz
zr4468_164V1V3_R2.fastq.gz
S165
zr4468_165V1V3_R1.fastq.gz
zr4468_165V1V3_R2.fastq.gz
S166
zr4468_166V1V3_R1.fastq.gz
zr4468_166V1V3_R2.fastq.gz
S167
zr4468_167V1V3_R1.fastq.gz
zr4468_167V1V3_R2.fastq.gz
S168
zr4468_168V1V3_R1.fastq.gz
zr4468_168V1V3_R2.fastq.gz
S169
zr4468_169V1V3_R1.fastq.gz
zr4468_169V1V3_R2.fastq.gz
S016
zr4468_16V1V3_R1.fastq.gz
zr4468_16V1V3_R2.fastq.gz
S170
zr4468_170V1V3_R1.fastq.gz
zr4468_170V1V3_R2.fastq.gz
S171
zr4468_171V1V3_R1.fastq.gz
zr4468_171V1V3_R2.fastq.gz
S172
zr4468_172V1V3_R1.fastq.gz
zr4468_172V1V3_R2.fastq.gz
S173
zr4468_173V1V3_R1.fastq.gz
zr4468_173V1V3_R2.fastq.gz
S174
zr4468_174V1V3_R1.fastq.gz
zr4468_174V1V3_R2.fastq.gz
S175
zr4468_175V1V3_R1.fastq.gz
zr4468_175V1V3_R2.fastq.gz
S176
zr4468_176V1V3_R1.fastq.gz
zr4468_176V1V3_R2.fastq.gz
S177
zr4468_177V1V3_R1.fastq.gz
zr4468_177V1V3_R2.fastq.gz
S178
zr4468_178V1V3_R1.fastq.gz
zr4468_178V1V3_R2.fastq.gz
S179
zr4468_179V1V3_R1.fastq.gz
zr4468_179V1V3_R2.fastq.gz
S017
zr4468_17V1V3_R1.fastq.gz
zr4468_17V1V3_R2.fastq.gz
S180
zr4468_180V1V3_R1.fastq.gz
zr4468_180V1V3_R2.fastq.gz
S181
zr4468_181V1V3_R1.fastq.gz
zr4468_181V1V3_R2.fastq.gz
S182
zr4468_182V1V3_R1.fastq.gz
zr4468_182V1V3_R2.fastq.gz
S183
zr4468_183V1V3_R1.fastq.gz
zr4468_183V1V3_R2.fastq.gz
S184
zr4468_184V1V3_R1.fastq.gz
zr4468_184V1V3_R2.fastq.gz
S185
zr4468_185V1V3_R1.fastq.gz
zr4468_185V1V3_R2.fastq.gz
S186
zr4468_186V1V3_R1.fastq.gz
zr4468_186V1V3_R2.fastq.gz
S187
zr4468_187V1V3_R1.fastq.gz
zr4468_187V1V3_R2.fastq.gz
S188
zr4468_188V1V3_R1.fastq.gz
zr4468_188V1V3_R2.fastq.gz
S189
zr4468_189V1V3_R1.fastq.gz
zr4468_189V1V3_R2.fastq.gz
S018
zr4468_18V1V3_R1.fastq.gz
zr4468_18V1V3_R2.fastq.gz
S190
zr4468_190V1V3_R1.fastq.gz
zr4468_190V1V3_R2.fastq.gz
S191
zr4468_191V1V3_R1.fastq.gz
zr4468_191V1V3_R2.fastq.gz
S192
zr4468_192V1V3_R1.fastq.gz
zr4468_192V1V3_R2.fastq.gz
S193
zr4468_193V1V3_R1.fastq.gz
zr4468_193V1V3_R2.fastq.gz
S194
zr4468_194V1V3_R1.fastq.gz
zr4468_194V1V3_R2.fastq.gz
S195
zr4468_195V1V3_R1.fastq.gz
zr4468_195V1V3_R2.fastq.gz
S196
zr4468_196V1V3_R1.fastq.gz
zr4468_196V1V3_R2.fastq.gz
S197
zr4468_197V1V3_R1.fastq.gz
zr4468_197V1V3_R2.fastq.gz
S198
zr4468_198V1V3_R1.fastq.gz
zr4468_198V1V3_R2.fastq.gz
S199
zr4468_199V1V3_R1.fastq.gz
zr4468_199V1V3_R2.fastq.gz
S019
zr4468_19V1V3_R1.fastq.gz
zr4468_19V1V3_R2.fastq.gz
S001
zr4468_1V1V3_R1.fastq.gz
zr4468_1V1V3_R2.fastq.gz
S200
zr4468_200V1V3_R1.fastq.gz
zr4468_200V1V3_R2.fastq.gz
S201
zr4468_201V1V3_R1.fastq.gz
zr4468_201V1V3_R2.fastq.gz
S202
zr4468_202V1V3_R1.fastq.gz
zr4468_202V1V3_R2.fastq.gz
S203
zr4468_203V1V3_R1.fastq.gz
zr4468_203V1V3_R2.fastq.gz
S204
zr4468_204V1V3_R1.fastq.gz
zr4468_204V1V3_R2.fastq.gz
S205
zr4468_205V1V3_R1.fastq.gz
zr4468_205V1V3_R2.fastq.gz
S206
zr4468_206V1V3_R1.fastq.gz
zr4468_206V1V3_R2.fastq.gz
S207
zr4468_207V1V3_R1.fastq.gz
zr4468_207V1V3_R2.fastq.gz
S208
zr4468_208V1V3_R1.fastq.gz
zr4468_208V1V3_R2.fastq.gz
S209
zr4468_209V1V3_R1.fastq.gz
zr4468_209V1V3_R2.fastq.gz
S020
zr4468_20V1V3_R1.fastq.gz
zr4468_20V1V3_R2.fastq.gz
S210
zr4468_210V1V3_R1.fastq.gz
zr4468_210V1V3_R2.fastq.gz
S211
zr4468_211V1V3_R1.fastq.gz
zr4468_211V1V3_R2.fastq.gz
S212
zr4468_212V1V3_R1.fastq.gz
zr4468_212V1V3_R2.fastq.gz
S213
zr4468_213V1V3_R1.fastq.gz
zr4468_213V1V3_R2.fastq.gz
S214
zr4468_214V1V3_R1.fastq.gz
zr4468_214V1V3_R2.fastq.gz
S215
zr4468_215V1V3_R1.fastq.gz
zr4468_215V1V3_R2.fastq.gz
S216
zr4468_216V1V3_R1.fastq.gz
zr4468_216V1V3_R2.fastq.gz
S217
zr4468_217V1V3_R1.fastq.gz
zr4468_217V1V3_R2.fastq.gz
S218
zr4468_218V1V3_R1.fastq.gz
zr4468_218V1V3_R2.fastq.gz
S219
zr4468_219V1V3_R1.fastq.gz
zr4468_219V1V3_R2.fastq.gz
S021
zr4468_21V1V3_R1.fastq.gz
zr4468_21V1V3_R2.fastq.gz
S220
zr4468_220V1V3_R1.fastq.gz
zr4468_220V1V3_R2.fastq.gz
S221
zr4468_221V1V3_R1.fastq.gz
zr4468_221V1V3_R2.fastq.gz
S222
zr4468_222V1V3_R1.fastq.gz
zr4468_222V1V3_R2.fastq.gz
S223
zr4468_223V1V3_R1.fastq.gz
zr4468_223V1V3_R2.fastq.gz
S224
zr4468_224V1V3_R1.fastq.gz
zr4468_224V1V3_R2.fastq.gz
S225
zr4468_225V1V3_R1.fastq.gz
zr4468_225V1V3_R2.fastq.gz
S226
zr4468_226V1V3_R1.fastq.gz
zr4468_226V1V3_R2.fastq.gz
S227
zr4468_227V1V3_R1.fastq.gz
zr4468_227V1V3_R2.fastq.gz
S228
zr4468_228V1V3_R1.fastq.gz
zr4468_228V1V3_R2.fastq.gz
S229
zr4468_229V1V3_R1.fastq.gz
zr4468_229V1V3_R2.fastq.gz
S022
zr4468_22V1V3_R1.fastq.gz
zr4468_22V1V3_R2.fastq.gz
S230
zr4468_230V1V3_R1.fastq.gz
zr4468_230V1V3_R2.fastq.gz
S231
zr4468_231V1V3_R1.fastq.gz
zr4468_231V1V3_R2.fastq.gz
S232
zr4468_232V1V3_R1.fastq.gz
zr4468_232V1V3_R2.fastq.gz
S233
zr4468_233V1V3_R1.fastq.gz
zr4468_233V1V3_R2.fastq.gz
S234
zr4468_234V1V3_R1.fastq.gz
zr4468_234V1V3_R2.fastq.gz
S235
zr4468_235V1V3_R1.fastq.gz
zr4468_235V1V3_R2.fastq.gz
S236
zr4468_236V1V3_R1.fastq.gz
zr4468_236V1V3_R2.fastq.gz
S237
zr4468_237V1V3_R1.fastq.gz
zr4468_237V1V3_R2.fastq.gz
S238
zr4468_238V1V3_R1.fastq.gz
zr4468_238V1V3_R2.fastq.gz
S239
zr4468_239V1V3_R1.fastq.gz
zr4468_239V1V3_R2.fastq.gz
S023
zr4468_23V1V3_R1.fastq.gz
zr4468_23V1V3_R2.fastq.gz
S240
zr4468_240V1V3_R1.fastq.gz
zr4468_240V1V3_R2.fastq.gz
S241
zr4468_241V1V3_R1.fastq.gz
zr4468_241V1V3_R2.fastq.gz
S242
zr4468_242V1V3_R1.fastq.gz
zr4468_242V1V3_R2.fastq.gz
S243
zr4468_243V1V3_R1.fastq.gz
zr4468_243V1V3_R2.fastq.gz
S244
zr4468_244V1V3_R1.fastq.gz
zr4468_244V1V3_R2.fastq.gz
S245
zr4468_245V1V3_R1.fastq.gz
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Please download and save the file to your computer storage device. The download link will expire after 60 days upon your receiving of this report.
DADA2 is a software package that models and corrects Illumina-sequenced amplicon errors.
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 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”.
Below is the link to a PDF file for viewing the quality plots for all samples:
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
281
271
261
251
241
231
321
38.49%
47.31%
47.98%
48.28%
48.66%
42.50%
311
38.63%
47.63%
48.36%
48.36%
42.82%
21.41%
301
38.69%
48.02%
47.71%
42.11%
21.46%
9.64%
291
38.96%
47.60%
41.82%
20.64%
9.75%
7.45%
281
38.74%
41.66%
20.51%
9.72%
7.48%
3.05%
271
33.28%
21.22%
9.43%
7.29%
3.03%
1.77%
Based on the above result, the trim length combination of R1 = 321 bases and R2 = 241 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
F4468.S001
F4468.S002
F4468.S003
F4468.S004
F4468.S005
F4468.S006
F4468.S007
F4468.S008
F4468.S009
F4468.S010
F4468.S011
F4468.S012
F4468.S013
F4468.S014
F4468.S015
F4468.S016
F4468.S017
F4468.S018
F4468.S019
F4468.S020
F4468.S021
F4468.S022
F4468.S023
F4468.S024
F4468.S025
F4468.S026
F4468.S027
F4468.S028
F4468.S029
F4468.S030
F4468.S031
F4468.S032
F4468.S033
F4468.S034
F4468.S035
F4468.S036
F4468.S037
F4468.S038
F4468.S039
F4468.S040
F4468.S041
F4468.S042
F4468.S043
F4468.S044
F4468.S045
F4468.S046
F4468.S047
F4468.S048
F4468.S049
F4468.S050
F4468.S051
F4468.S052
F4468.S053
F4468.S054
F4468.S055
F4468.S056
F4468.S057
F4468.S058
F4468.S059
F4468.S060
F4468.S061
F4468.S062
F4468.S063
F4468.S064
F4468.S065
F4468.S066
F4468.S067
F4468.S068
F4468.S069
F4468.S070
F4468.S071
F4468.S072
F4468.S073
F4468.S074
F4468.S075
F4468.S076
F4468.S077
F4468.S078
F4468.S079
F4468.S080
F4468.S081
F4468.S082
F4468.S083
F4468.S084
F4468.S085
F4468.S086
F4468.S087
F4468.S088
F4468.S089
F4468.S090
F4468.S091
F4468.S092
F4468.S093
F4468.S094
F4468.S095
F4468.S096
F4468.S097
F4468.S098
F4468.S099
F4468.S100
F4468.S101
F4468.S102
F4468.S103
F4468.S104
F4468.S105
F4468.S106
F4468.S107
F4468.S108
F4468.S109
F4468.S110
F4468.S111
F4468.S112
F4468.S113
F4468.S114
F4468.S115
F4468.S116
F4468.S117
F4468.S118
F4468.S119
F4468.S120
F4468.S121
F4468.S122
F4468.S123
F4468.S124
F4468.S125
F4468.S126
F4468.S127
F4468.S128
F4468.S129
F4468.S130
F4468.S131
F4468.S132
F4468.S133
F4468.S134
F4468.S135
F4468.S136
F4468.S137
F4468.S138
F4468.S139
F4468.S140
F4468.S141
F4468.S142
F4468.S143
F4468.S144
F4468.S145
F4468.S146
F4468.S147
F4468.S148
F4468.S149
F4468.S150
F4468.S151
F4468.S152
F4468.S153
F4468.S154
F4468.S155
F4468.S156
F4468.S157
F4468.S158
F4468.S159
F4468.S160
F4468.S161
F4468.S162
F4468.S163
F4468.S164
F4468.S165
F4468.S166
F4468.S167
F4468.S168
F4468.S169
F4468.S170
F4468.S171
F4468.S172
F4468.S173
F4468.S174
F4468.S175
F4468.S176
F4468.S177
F4468.S178
F4468.S179
F4468.S180
F4468.S181
F4468.S182
F4468.S183
F4468.S184
F4468.S185
F4468.S186
F4468.S187
F4468.S188
F4468.S189
F4468.S190
F4468.S191
F4468.S192
F4468.S193
F4468.S194
F4468.S195
F4468.S196
F4468.S197
F4468.S198
F4468.S199
F4468.S200
F4468.S201
F4468.S202
F4468.S203
F4468.S204
F4468.S205
F4468.S206
F4468.S207
F4468.S208
F4468.S209
F4468.S210
F4468.S211
F4468.S212
F4468.S213
F4468.S214
F4468.S215
F4468.S216
F4468.S217
F4468.S218
F4468.S219
F4468.S220
F4468.S221
F4468.S222
F4468.S223
F4468.S224
F4468.S225
F4468.S226
F4468.S227
F4468.S228
F4468.S229
F4468.S230
F4468.S231
F4468.S232
F4468.S233
F4468.S234
F4468.S235
F4468.S236
F4468.S237
F4468.S238
F4468.S239
F4468.S240
F4468.S241
F4468.S242
F4468.S243
F4468.S244
F4468.S245
F4468.S246
F4468.S247
F4468.S248
F4468.S249
F4468.S250
F4468.S251
F4468.S252
F4468.S253
F4468.S254
F4468.S255
F4468.S256
F4468.S257
F4468.S258
F4468.S259
F4468.S260
F4468.S261
F4468.S262
F4468.S263
F4468.S264
F4468.S265
F4468.S266
F4468.S267
F4468.S268
F4468.S269
F4468.S270
Row Sum
Percentage
input
56,167
53,762
61,973
64,390
61,725
52,771
66,084
55,584
2,837
187
52,297
59,662
52,873
51,855
57,736
54,073
55,293
46,903
308
318
54,154
51,725
56,848
49,306
52,093
48,901
50,725
53,462
4,091
214
54,736
46,875
66,013
60,851
67,646
69,439
67,637
62,681
115,753
1,266
56,025
55,315
55,412
51,884
63,774
54,983
62,704
55,626
383
155
62,266
53,824
52,784
53,312
53,889
59,864
68,911
57,635
87,445
45,940
54,360
51,013
55,726
59,501
56,543
51,002
53,207
57,130
13,590
232
66,384
64,904
57,985
49,987
53,960
53,117
51,369
44,185
285
258
59,439
57,812
52,669
59,702
59,430
60,718
63,054
57,120
15,655
38,440
39,480
41,547
36,654
38,939
45,962
55,477
71,537
55,123
59,516
50,664
68,288
70,055
47,041
48,922
58,351
53,876
68,737
53,572
132
152
48,866
49,491
47,052
49,125
59,569
46,939
61,635
56,540
179
196
43,404
44,173
43,475
50,605
54,348
50,356
61,430
56,332
383
221
61,971
55,724
71,717
70,675
63,438
54,407
59,540
52,243
223
183
70,485
65,944
44,614
49,551
51,366
43,598
45,387
53,031
161
130
51,642
45,124
44,366
42,134
56,276
53,462
62,917
56,136
59,918
9,572
56,572
52,875
54,773
49,475
55,231
62,985
51,764
42,542
37,601
151
49,139
43,741
54,616
57,886
60,325
56,219
61,169
49,636
225
4,439
67,186
62,841
40,991
34,174
44,081
44,297
44,668
37,216
8,516
14,553
45,763
45,130
44,494
49,018
44,902
49,920
51,747
39,131
147
246
38,152
43,125
42,905
43,315
49,864
45,655
46,744
42,059
51,174
44,610
51,214
47,258
43,324
39,505
48,056
49,964
48,269
30,755
43,111
248
51,628
47,453
49,643
50,607
49,531
47,917
55,155
51,326
61,325
144
54,194
61,155
47,362
51,877
64,475
64,723
43,493
38,176
141
110
36,338
34,231
54,778
46,165
54,434
46,329
53,967
46,836
121
133
52,979
50,873
58,017
48,506
48,749
52,613
47,075
48,868
7,939
178
50,474
45,596
43,665
43,430
46,481
49,908
41,438
42,355
32
23
12,159,059
100.00%
filtered
44,657
43,361
49,053
50,900
48,559
42,754
52,236
43,053
38
36
41,240
46,638
41,435
41,065
45,608
42,449
42,734
35,832
61
58
41,474
40,313
44,122
38,398
40,041
38,048
39,692
41,102
57
39
42,911
36,044
51,787
48,332
54,160
55,740
53,972
49,614
91,996
788
43,609
43,066
43,435
40,634
48,372
43,236
49,397
43,654
153
19
46,639
39,221
39,689
41,231
40,650
44,593
53,625
44,755
65,070
34,701
42,626
39,341
43,279
46,873
45,429
39,950
42,082
45,531
606
57
52,478
51,034
45,419
39,469
42,198
40,082
39,577
34,824
67
47
46,930
46,206
41,114
46,723
46,407
47,901
50,077
44,673
11,962
30,436
30,751
32,556
28,733
31,059
32,826
43,514
55,977
43,545
46,780
39,842
53,813
55,925
36,764
38,776
44,524
42,456
54,656
42,719
32
33
37,388
38,747
36,615
38,793
47,082
36,657
48,229
45,061
58
52
33,820
34,527
33,699
39,353
41,665
38,940
46,615
45,121
154
49
48,428
43,413
56,272
55,845
50,089
43,651
46,102
40,423
76
56
56,668
50,953
33,082
37,914
40,245
34,362
35,492
41,039
25
20
39,439
35,877
34,503
32,738
44,014
41,930
49,404
43,430
47,017
362
45,198
42,365
43,657
39,524
44,003
50,904
40,132
33,587
26,582
37
37,690
34,375
42,038
46,330
47,722
44,318
48,524
39,647
50
47
52,932
49,508
31,766
26,968
34,764
35,190
34,962
29,475
419
1,611
35,364
34,500
34,903
38,020
35,070
38,271
40,676
30,025
28
77
28,469
32,964
32,448
32,714
36,842
33,834
34,741
30,688
32,439
31,855
40,024
34,943
33,722
30,531
37,311
38,933
37,053
23,990
33,238
100
40,066
37,016
38,528
39,647
38,892
37,719
43,574
40,538
48,608
34
43,068
48,615
37,082
41,269
51,047
51,231
34,435
30,330
20
22
29,026
27,431
43,610
36,859
43,032
36,690
42,300
37,103
25
35
41,225
39,822
45,195
38,107
38,419
41,427
36,980
38,867
77
31
39,388
36,034
34,189
34,429
35,494
39,222
32,772
33,459
14
11
9,441,431
77.65%
denoisedF
43,868
42,577
48,042
50,006
47,872
42,362
50,998
41,975
2
2
40,190
45,788
40,476
40,245
44,663
41,702
42,018
34,947
5
2
39,963
39,046
42,600
37,236
38,590
36,714
38,507
39,588
14
8
41,600
35,128
50,526
47,320
53,492
54,917
53,244
48,617
89,836
597
42,315
41,656
42,058
39,261
46,915
41,491
47,991
42,217
37
1
45,809
37,908
38,650
40,282
39,616
43,767
52,521
43,947
62,951
33,304
41,342
38,103
41,956
45,936
44,142
38,761
40,785
44,510
78
21
51,282
49,810
44,492
38,568
41,434
39,487
38,697
33,952
10
5
45,673
44,883
39,950
45,717
45,256
46,467
48,654
43,438
11,384
29,240
29,441
31,446
28,010
30,137
31,724
42,131
54,319
42,393
45,484
38,694
52,493
54,819
36,123
38,241
43,623
41,493
53,958
41,726
3
1
36,206
37,939
35,660
37,992
46,425
35,991
47,381
44,193
2
11
33,007
33,801
32,905
38,322
40,657
37,993
45,765
44,173
103
8
46,250
41,783
54,606
53,817
48,913
42,664
44,321
38,708
16
10
56,124
50,284
32,555
37,299
39,700
33,863
35,091
40,389
1
2
38,123
34,837
33,328
31,787
42,645
40,655
48,218
42,162
45,713
73
44,444
41,454
43,135
38,867
43,191
49,965
39,288
33,143
25,263
7
37,170
33,857
41,230
45,690
47,155
43,740
47,841
39,099
3
2
52,077
48,617
31,160
26,390
34,147
34,481
34,328
28,907
43
166
34,578
33,643
34,023
37,009
34,311
37,065
40,091
29,198
1
35
27,549
31,871
31,174
31,677
35,772
32,848
33,765
29,938
31,382
30,952
38,871
34,050
32,758
29,562
36,255
37,642
35,924
23,047
31,872
57
39,312
36,151
37,672
38,979
38,140
36,978
42,726
39,695
47,330
11
42,049
47,527
36,109
40,470
49,704
50,201
33,574
29,535
1
3
28,137
26,824
42,809
35,992
42,107
35,876
41,287
36,365
2
2
40,377
39,144
44,068
37,204
37,807
40,631
36,089
38,014
1
1
38,744
35,481
33,522
33,816
34,962
38,468
31,963
32,765
1
4
9,211,153
75.76%
denoisedR
44,310
42,933
48,440
50,264
48,128
42,604
51,341
42,357
16
6
40,829
46,147
40,786
40,473
44,966
41,921
42,187
35,280
1
9
40,828
39,631
43,301
37,809
39,043
37,232
39,050
40,313
32
6
42,401
35,511
51,061
47,863
53,684
55,319
53,529
49,234
90,831
690
42,756
42,201
42,435
39,819
47,670
42,213
48,606
42,657
57
2
45,871
38,210
38,769
40,668
40,007
44,006
52,946
44,231
63,683
33,446
41,758
38,482
42,412
46,328
44,765
39,159
41,371
44,847
446
30
51,797
50,176
44,997
39,030
41,759
39,624
39,095
34,209
22
17
46,309
45,521
40,453
46,202
45,773
47,244
49,398
44,036
11,597
29,740
29,949
31,771
28,215
30,634
31,898
42,572
54,964
42,818
45,874
39,114
53,032
55,097
36,276
38,237
43,877
41,793
54,295
42,222
3
15
36,668
38,209
36,058
38,437
46,682
36,277
47,779
44,622
16
25
33,188
33,848
33,076
38,635
40,978
38,217
45,904
44,381
103
13
47,130
42,511
55,269
55,008
49,370
43,045
45,302
39,670
31
10
56,328
50,481
32,880
37,550
39,952
34,062
35,224
40,587
1
1
38,821
35,504
33,768
32,267
43,356
41,369
48,575
42,781
46,147
294
44,793
41,976
43,331
39,063
43,600
50,466
39,706
33,325
25,973
20
37,353
34,152
41,564
46,050
47,424
43,909
48,013
39,379
9
2
52,363
48,747
31,372
26,586
34,400
34,797
34,561
29,140
268
1,403
34,774
34,146
34,497
37,502
34,646
37,567
40,303
29,500
1
33
27,784
32,154
31,676
32,073
36,149
33,121
34,042
30,172
31,426
31,245
39,417
34,252
33,079
29,776
36,697
38,230
36,287
23,368
32,268
58
39,620
36,410
38,129
39,254
38,437
37,216
42,899
39,995
47,747
15
42,492
48,066
36,417
40,659
50,189
50,508
33,821
29,743
2
3
28,641
27,069
43,161
36,419
42,557
36,120
41,587
36,608
11
4
40,666
39,452
44,450
37,534
38,000
41,117
36,494
38,471
22
1
38,944
35,611
33,828
34,017
35,088
38,680
32,295
32,956
1
2
9,301,698
76.50%
merged
41,689
41,016
45,250
46,755
45,188
41,956
45,896
37,893
0
2
37,641
42,938
37,214
37,147
41,411
39,221
39,700
31,474
0
0
36,909
35,606
38,824
34,229
34,515
33,499
36,132
36,500
13
2
39,101
32,341
46,249
43,793
50,596
52,997
51,873
43,697
80,653
536
38,069
36,940
37,858
35,684
42,357
37,000
44,436
37,815
25
0
41,623
34,201
34,598
37,459
35,834
39,044
47,625
41,193
54,828
27,515
38,558
34,891
38,881
42,987
41,799
35,646
37,844
42,131
11
21
48,781
47,029
42,597
36,889
39,951
37,939
37,176
31,686
5
5
42,997
42,415
37,327
42,835
41,431
43,237
45,966
40,216
10,561
26,670
26,132
28,749
26,305
28,557
28,805
38,527
50,326
39,839
42,711
36,557
49,654
51,254
34,105
36,113
41,280
39,021
52,459
39,459
0
0
33,434
35,737
32,712
35,784
44,509
34,120
44,958
41,586
2
11
30,434
31,354
30,275
35,191
37,362
34,513
41,758
41,133
61
0
39,817
37,251
49,791
48,347
45,928
40,379
39,465
34,985
14
5
53,953
47,343
29,876
35,050
36,896
32,095
33,474
38,016
0
0
35,914
33,071
29,793
28,546
39,371
37,894
44,935
37,328
41,506
24
42,620
39,654
41,061
36,829
40,743
47,852
37,473
31,416
23,331
6
23,481
29,790
31,033
41,697
44,878
27,721
38,612
33,234
3
2
39,152
26,408
22,410
17,154
24,185
26,900
23,987
23,279
14
63
32,607
32,332
32,295
34,857
32,843
34,454
38,564
27,341
1
27
25,255
28,935
28,491
29,168
33,305
30,364
31,316
27,806
28,101
28,416
36,280
30,798
29,375
26,049
33,543
34,911
32,627
19,946
27,563
25
38,213
33,758
35,533
37,126
36,911
35,346
40,224
37,863
44,101
11
40,167
45,342
33,315
37,678
46,486
47,194
31,187
27,699
0
3
26,505
25,624
40,280
33,541
40,102
33,856
37,852
33,977
0
2
38,123
36,925
41,038
34,677
36,432
39,128
33,665
36,394
0
0
37,615
34,494
31,607
32,237
34,227
36,911
29,663
30,918
0
2
8,465,431
69.62%
nonchim
26,394
26,708
27,821
26,236
20,931
29,620
24,198
17,669
0
2
24,454
28,940
23,148
23,510
26,966
26,172
26,360
16,908
0
0
23,951
23,838
24,725
22,733
20,938
22,622
24,024
24,656
13
2
25,404
20,792
29,043
25,919
33,241
35,385
35,549
23,898
45,458
390
21,729
21,561
22,012
20,756
24,157
22,885
23,210
17,476
12
0
24,713
20,344
21,549
22,413
20,270
23,902
30,666
25,656
29,395
15,968
24,287
19,914
24,074
26,559
23,285
22,630
19,774
22,195
11
10
27,209
25,213
23,105
21,798
21,143
20,450
20,459
18,525
5
5
25,484
23,717
22,430
26,000
24,113
26,580
26,989
22,060
4,675
12,140
16,928
18,832
16,230
16,741
17,745
22,209
30,748
21,693
23,520
15,799
31,072
28,718
22,419
24,683
26,741
25,288
31,399
24,419
0
0
21,861
23,394
17,835
18,884
28,173
20,807
25,581
19,572
0
11
19,072
20,411
18,517
20,600
24,078
20,953
22,809
20,925
61
0
19,615
18,461
26,805
24,449
30,913
27,380
20,973
16,006
14
5
33,671
25,545
17,200
20,632
22,768
20,975
21,381
25,113
0
0
21,408
19,554
17,918
17,667
23,293
22,635
25,992
21,568
20,922
17
28,035
26,546
26,558
24,525
29,756
31,633
23,612
20,992
13,480
6
16,397
24,435
22,071
36,606
30,414
19,514
28,675
21,874
3
2
26,961
18,533
16,234
12,854
18,115
21,657
17,435
15,796
14
63
20,706
21,120
20,644
22,191
21,171
22,483
23,405
15,051
1
14
16,620
18,908
19,144
19,255
21,698
20,597
20,707
17,427
13,915
14,034
24,110
17,961
18,920
14,832
22,000
22,782
21,411
11,896
13,124
15
22,246
22,147
23,042
24,454
22,126
22,755
25,273
25,036
27,220
0
28,038
29,623
18,981
22,618
27,497
29,152
16,443
12,363
0
3
16,160
16,357
23,073
18,744
24,706
21,434
19,740
18,934
0
2
25,224
24,945
26,316
23,071
24,411
25,031
18,113
21,417
0
0
24,180
22,307
20,231
22,227
21,639
24,892
19,478
18,102
0
2
5,172,430
42.54%
This table can be downloaded as an Excel table below:
5. DADA2 Amplicon Sequence Variants (ASVs). A total of 34282 unique merged and chimera-free ASV sequences were identified, and their corresponding
read counts for each sample are available in the "ASV Read Count Table" with rows for the ASV sequences and columns for sample. This read count table can be used for
microbial profile comparison among different samples and the sequences provided in the table can be used to taxonomy assignment.
The species-level, open-reference 16S rRNA NGS reads taxonomy assignment pipeline
Version 20210310
1. Raw sequences reads in FASTA format were BLASTN-searched against a combined set of 16S rRNA reference sequences.
It consists of MOMD (version 0.1), the HOMD (version 15.2 http://www.homd.org/index.php?name=seqDownload&file&type=R ),
HOMD 16S rRNA RefSeq Extended Version 1.1 (EXT), GreenGene Gold (GG)
(http://greengenes.lbl.gov/Download/Sequence_Data/Fasta_data_files/gold_strains_gg16S_aligned.fasta.gz) ,
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 from HOMD V15.22, 495 from EXT, 3,940 from GG and 18,044 from NCBI, a total of 25,120 sequences.
Altogether these sequence represent a total of 15,601 oral and non-oral microbial species.
The NCBI BLASTN version 2.7.1+ (Zhang et al, 2000) 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).
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:
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
Read Count (MC=1)*
Read Count (MC=100)*
A
Total reads
5,172,430
5,172,430
B
Total assigned reads
5,152,216
5,152,216
C
Assigned reads in species with read count < MC
0
10,200
D
Assigned reads in samples with read count < 500
529
509
E
Total samples
250
250
F
Samples with reads >= 500
229
229
G
Samples with reads < 500
21
21
H
Total assigned reads used for analysis (B-C-D)
5,151,687
5,141,507
I
Reads assigned to single species
4,697,805
4,693,469
J
Reads assigned to multiple species
409,628
409,097
K
Reads assigned to novel species
44,254
38,941
L
Total number of species
985
363
M
Number of single species
451
300
N
Number of multi-species
41
16
O
Number of novel species
488
47
P
Total unassigned reads
20,214
20,214
Q
Chimeric reads
627
627
R
Reads without BLASTN hits
1,153
1,153
S
Others: short, low quality, singletons, etc.
18,434
18,434
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
* MC = Minimal Count per species, species with total read count < MC were removed.
* The assignment result from MC=100 was used in the downstream analyses.
Read Taxonomy Assignment - Sample Meta Information
#SampleID
Sample_Name
Group1
Group2
Group3
Group4
F4468.S001
105.BV0.RBX
105
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S002
105.BV0.LBX
105
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S003
105.BV0.RLT
105
Baseline Visit
Right Tongue
BV0-RLT
F4468.S004
105.BV0.LLT
105
Baseline Visit
Left Tongue
BV0-LLT
F4468.S005
105.BV0.ULP
105
Baseline Visit
Upper Lip
BV0-ULP
F4468.S006
105.BV0.LLP
105
Baseline Visit
Lower Lip
BV0-LLP
F4468.S007
105.BV0.FOM
105
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S008
105.BV0.THR
105
Baseline Visit
Throat
BV0-THR
F4468.S009
105.BV0.SLP
105
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S010
105.BV0.SSP
105
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S011
121.BV0.RBX
121
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S012
121.BV0.LBX
121
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S013
121.BV0.RLT
121
Baseline Visit
Right Tongue
BV0-RLT
F4468.S014
121.BV0.LLT
121
Baseline Visit
Left Tongue
BV0-LLT
F4468.S015
121.BV0.ULP
121
Baseline Visit
Upper Lip
BV0-ULP
F4468.S016
121.BV0.LLP
121
Baseline Visit
Lower Lip
BV0-LLP
F4468.S017
121.BV0.FOM
121
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S018
121.BV0.THR
121
Baseline Visit
Throat
BV0-THR
F4468.S019
121.BV0.SLP
121
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S020
121.BV0.SSP
121
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S021
108.BV0.RBX
108
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S022
108.BV0.LBX
108
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S023
108.BV0.RLT
108
Baseline Visit
Right Tongue
BV0-RLT
F4468.S024
108.BV0.LLT
108
Baseline Visit
Left Tongue
BV0-LLT
F4468.S025
108.BV0.ULP
108
Baseline Visit
Upper Lip
BV0-ULP
F4468.S026
108.BV0.LLP
108
Baseline Visit
Lower Lip
BV0-LLP
F4468.S027
108.BV0.FOM
108
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S028
108.BV0.THR
108
Baseline Visit
Throat
BV0-THR
F4468.S029
108.BV0.SLP
108
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S030
108.BV0.SSP
108
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S031
108.FIV.RBX
108
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S032
108.FIV.LBX
108
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S033
108.FIV.RLT
108
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S034
108.FIV.LLT
108
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S035
108.FIV.ULP
108
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S036
108.FIV.LLP
108
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S037
108.FIV.FOM
108
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S038
108.FIV.THR
108
Final Intervention Visit
Throat
FIV-THR
F4468.S039
108.FIV.SLP
108
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S040
108.FIV.SSP
108
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S041
108.PIV.RBX
108
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S042
108.PIV.LBX
108
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S043
108.PIV.RLT
108
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S044
108.PIV.LLT
108
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S045
108.PIV.ULP
108
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S046
108.PIV.LLP
108
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S047
108.PIV.FOM
108
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S048
108.PIV.THR
108
Post Intervention Visit
Throat
PIV-THR
F4468.S049
108.PIV.SLP
108
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S050
108.PIV.SSP
108
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
F4468.S051
105.FIV.RBX
105
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S052
105.FIV.LBX
105
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S053
105.FIV.RLT
105
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S054
105.FIV.LLT
105
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S055
105.FIV.ULP
105
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S056
105.FIV.LLP
105
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S057
105.FIV.FOM
105
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S058
105.FIV.THR
105
Final Intervention Visit
Throat
FIV-THR
F4468.S059
105.FIV.SLP
105
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S060
105.FIV.SSP
105
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S061
105.PIV.RBX
105
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S062
105.PIV.LBX
105
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S063
105.PIV.RLT
105
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S064
105.PIV.LLT
105
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S065
105.PIV.ULP
105
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S066
105.PIV.LLP
105
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S067
105.PIV.FOM
105
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S068
105.PIV.THR
105
Post Intervention Visit
Throat
PIV-THR
F4468.S069
105.PIV.SLP
105
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S070
105.PIV.SSP
105
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
F4468.S071
110.BV0.RBX
110
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S072
110.BV0.LBX
110
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S073
110.BV0.RLT
110
Baseline Visit
Right Tongue
BV0-RLT
F4468.S074
110.BV0.LLT
110
Baseline Visit
Left Tongue
BV0-LLT
F4468.S075
110.BV0.ULP
110
Baseline Visit
Upper Lip
BV0-ULP
F4468.S076
110.BV0.LLP
110
Baseline Visit
Lower Lip
BV0-LLP
F4468.S077
110.BV0.FOM
110
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S078
110.BV0.THR
110
Baseline Visit
Throat
BV0-THR
F4468.S079
110.BV0.SLP
110
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S080
110.BV0.SSP
110
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S081
110.FIV.RBX
110
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S082
110.FIV.LBX
110
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S083
110.FIV.RLT
110
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S084
110.FIV.LLT
110
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S085
110.FIV.ULP
110
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S086
110.FIV.LLP
110
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S087
110.FIV.FOM
110
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S088
110.FIV.THR
110
Final Intervention Visit
Throat
FIV-THR
F4468.S089
110.FIV.SLP
110
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S090
110.FIV.SSP
110
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S091
110.PIV.RBX
110
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S092
110.PIV.LBX
110
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S093
110.PIV.RLT
110
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S094
110.PIV.LLT
110
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S095
110.PIV.ULP
110
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S096
110.PIV.LLP
110
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S097
110.PIV.FOM
110
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S098
110.PIV.THR
110
Post Intervention Visit
Throat
PIV-THR
F4468.S099
110.PIV.SLP
110
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S100
110.PIV.SSP
110
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
F4468.S101
118.BV0.RBX
118
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S102
118.BV0.LBX
118
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S103
118.BV0.RLT
118
Baseline Visit
Right Tongue
BV0-RLT
F4468.S104
118.BV0.LLT
118
Baseline Visit
Left Tongue
BV0-LLT
F4468.S105
118.BV0.ULP
118
Baseline Visit
Upper Lip
BV0-ULP
F4468.S106
118.BV0.LLP
118
Baseline Visit
Lower Lip
BV0-LLP
F4468.S107
118.BV0.FOM
118
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S108
118.BV0.THR
118
Baseline Visit
Throat
BV0-THR
F4468.S109
118.BV0.SLP
118
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S110
118.BV0.SSP
118
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S111
118.FIV.RBX
118
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S112
118.FIV.LBX
118
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S113
118.FIV.RLT
118
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S114
118.FIV.LLT
118
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S115
118.FIV.ULP
118
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S116
118.FIV.LLP
118
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S117
118.FIV.FOM
118
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S118
118.FIV.THR
118
Final Intervention Visit
Throat
FIV-THR
F4468.S119
118.FIV.SLP
118
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S120
118.FIV.SSP
118
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S121
118.PIV.RBX
118
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S122
118.PIV.LBX
118
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S123
118.PIV.RLT
118
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S124
118.PIV.LLT
118
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S125
118.PIV.ULP
118
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S126
118.PIV.LLP
118
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S127
118.PIV.FOM
118
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S128
118.PIV.THR
118
Post Intervention Visit
Throat
PIV-THR
F4468.S129
118.PIV.SLP
118
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S130
118.PIV.SSP
118
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
F4468.S131
114.BV0.RBX
114
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S132
114.BV0.LBX
114
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S133
114.BV0.RLT
114
Baseline Visit
Right Tongue
BV0-RLT
F4468.S134
114.BV0.LLT
114
Baseline Visit
Left Tongue
BV0-LLT
F4468.S135
114.BV0.ULP
114
Baseline Visit
Upper Lip
BV0-ULP
F4468.S136
114.BV0.LLP
114
Baseline Visit
Lower Lip
BV0-LLP
F4468.S137
114.BV0.FOM
114
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S138
114.BV0.THR
114
Baseline Visit
Throat
BV0-THR
F4468.S139
114.BV0.SLP
114
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S140
114.BV0.SSP
114
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S141
114.FIV.RBX
114
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S142
114.FIV.LBX
114
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S143
114.FIV.RLT
114
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S144
114.FIV.LLT
114
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S145
114.FIV.ULP
114
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S146
114.FIV.LLP
114
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S147
114.FIV.FOM
114
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S148
114.FIV.THR
114
Final Intervention Visit
Throat
FIV-THR
F4468.S149
114.FIV.SLP
114
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S150
114.FIV.SSP
114
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S151
114.PIV.RBX
114
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S152
114.PIV.LBX
114
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S153
114.PIV.RLT
114
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S154
114.PIV.LLT
114
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S155
114.PIV.ULP
114
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S156
114.PIV.LLP
114
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S157
114.PIV.FOM
114
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S158
114.PIV.THR
114
Post Intervention Visit
Throat
PIV-THR
F4468.S159
114.PIV.SLP
114
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S160
114.PIV.SSP
114
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
F4468.S161
120.BV0.RBX
120
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S162
120.BV0.LBX
120
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S163
120.BV0.RLT
120
Baseline Visit
Right Tongue
BV0-RLT
F4468.S164
120.BV0.LLT
120
Baseline Visit
Left Tongue
BV0-LLT
F4468.S165
120.BV0.ULP
120
Baseline Visit
Upper Lip
BV0-ULP
F4468.S166
120.BV0.LLP
120
Baseline Visit
Lower Lip
BV0-LLP
F4468.S167
120.BV0.FOM
120
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S168
120.BV0.THR
120
Baseline Visit
Throat
BV0-THR
F4468.S169
120.BV0.SLP
120
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S170
120.BV0.SSP
120
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S171
120.FIV.RBX
120
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S172
120.FIV.LBX
120
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S173
120.FIV.RLT
120
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S174
120.FIV.LLT
120
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S175
120.FIV.ULP
120
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S176
120.FIV.LLP
120
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S177
120.FIV.FOM
120
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S178
120.FIV.THR
120
Final Intervention Visit
Throat
FIV-THR
F4468.S179
120.FIV.SLP
120
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S180
120.FIV.SSP
120
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S181
120.PIV.RBX
120
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S182
120.PIV.LBX
120
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S183
120.PIV.RLT
120
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S184
120.PIV.LLT
120
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S185
120.PIV.ULP
120
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S186
120.PIV.LLP
120
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S187
120.PIV.FOM
120
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S188
120.PIV.THR
120
Post Intervention Visit
Throat
PIV-THR
F4468.S189
120.PIV.SLP
120
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S190
120.PIV.SSP
120
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
F4468.S191
121.FIV.RBX
121
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S192
121.FIV.LBX
121
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S193
121.FIV.RLT
121
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S194
121.FIV.LLT
121
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S195
121.FIV.ULP
121
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S196
121.FIV.LLP
121
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S197
121.FIV.FOM
121
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S198
121.FIV.THR
121
Final Intervention Visit
Throat
FIV-THR
F4468.S199
121.FIV.SLP
121
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S200
121.FIV.SSP
121
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S201
121.PIV.RBX
121
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S202
121.PIV.LBX
121
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S203
121.PIV.RLT
121
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S204
121.PIV.LLT
121
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S205
121.PIV.ULP
121
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S206
121.PIV.LLP
121
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S207
121.PIV.FOM
121
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S208
121.PIV.THR
121
Post Intervention Visit
Throat
PIV-THR
F4468.S209
121.PIV.SLP
121
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S210
121.PIV.SSP
121
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
F4468.S211
122.BV0.RBX
122
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S212
122.BV0.LBX
122
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S213
122.BV0.RLT
122
Baseline Visit
Right Tongue
BV0-RLT
F4468.S214
122.BV0.LLT
122
Baseline Visit
Left Tongue
BV0-LLT
F4468.S215
122.BV0.ULP
122
Baseline Visit
Upper Lip
BV0-ULP
F4468.S216
122.BV0.LLP
122
Baseline Visit
Lower Lip
BV0-LLP
F4468.S217
122.BV0.FOM
122
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S218
122.BV0.THR
122
Baseline Visit
Throat
BV0-THR
F4468.S219
122.BV0.SLP
122
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S220
122.BV0.SSP
122
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S221
122.FIV.RBX
122
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S222
122.FIV.LBX
122
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S223
122.FIV.RLT
122
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S224
122.FIV.LLT
122
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S225
122.FIV.ULP
122
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S226
122.FIV.LLP
122
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S227
122.FIV.FOM
122
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S228
122.FIV.THR
122
Final Intervention Visit
Throat
FIV-THR
F4468.S229
122.FIV.SLP
122
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S230
122.FIV.SSP
122
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S231
122.PIV.RBX
122
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S232
122.PIV.LBX
122
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S233
122.PIV.RLT
122
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S234
122.PIV.LLT
122
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S235
122.PIV.ULP
122
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S236
122.PIV.LLP
122
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S237
122.PIV.FOM
122
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S238
122.PIV.THR
122
Post Intervention Visit
Throat
PIV-THR
F4468.S239
122.PIV.SLP
122
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S240
122.PIV.SSP
122
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
F4468.S241
126.BV0.RBX
126
Baseline Visit
Right Buccal Mucosa
BV0-RBX
F4468.S242
126.BV0.LBX
126
Baseline Visit
Left Buccal Mucosa
BV0-LBX
F4468.S243
126.BV0.RLT
126
Baseline Visit
Right Tongue
BV0-RLT
F4468.S244
126.BV0.LLT
126
Baseline Visit
Left Tongue
BV0-LLT
F4468.S245
126.BV0.ULP
126
Baseline Visit
Upper Lip
BV0-ULP
F4468.S246
126.BV0.LLP
126
Baseline Visit
Lower Lip
BV0-LLP
F4468.S247
126.BV0.FOM
126
Baseline Visit
Floor of Mouth
BV0-FOM
F4468.S248
126.BV0.THR
126
Baseline Visit
Throat
BV0-THR
F4468.S249
126.BV0.SLP
126
Baseline Visit
Saline Rinse Pellet
BV0-SLP
F4468.S250
126.BV0.SSP
126
Baseline Visit
Stimulated Saliva Pellet
BV0-SSP
F4468.S251
126.FIV.RBX
126
Final Intervention Visit
Right Buccal Mucosa
FIV-RBX
F4468.S252
126.FIV.LBX
126
Final Intervention Visit
Left Buccal Mucosa
FIV-LBX
F4468.S253
126.FIV.RLT
126
Final Intervention Visit
Right Tongue
FIV-RLT
F4468.S254
126.FIV.LLT
126
Final Intervention Visit
Left Tongue
FIV-LLT
F4468.S255
126.FIV.ULP
126
Final Intervention Visit
Upper Lip
FIV-ULP
F4468.S256
126.FIV.LLP
126
Final Intervention Visit
Lower Lip
FIV-LLP
F4468.S257
126.FIV.FOM
126
Final Intervention Visit
Floor of Mouth
FIV-FOM
F4468.S258
126.FIV.THR
126
Final Intervention Visit
Throat
FIV-THR
F4468.S259
126.FIV.SLP
126
Final Intervention Visit
Saline Rinse Pellet
FIV-SLP
F4468.S260
126.FIV.SSP
126
Final Intervention Visit
Stimulated Saliva Pellet
FIV-SSP
F4468.S261
126.PIV.RBX
126
Post Intervention Visit
Right Buccal Mucosa
PIV-RBX
F4468.S262
126.PIV.LBX
126
Post Intervention Visit
Left Buccal Mucosa
PIV-LBX
F4468.S263
126.PIV.RLT
126
Post Intervention Visit
Right Tongue
PIV-RLT
F4468.S264
126.PIV.LLT
126
Post Intervention Visit
Left Tongue
PIV-LLT
F4468.S265
126.PIV.ULP
126
Post Intervention Visit
Upper Lip
PIV-ULP
F4468.S266
126.PIV.LLP
126
Post Intervention Visit
Lower Lip
PIV-LLP
F4468.S267
126.PIV.FOM
126
Post Intervention Visit
Floor of Mouth
PIV-FOM
F4468.S268
126.PIV.THR
126
Post Intervention Visit
Throat
PIV-THR
F4468.S269
126.PIV.SLP
126
Post Intervention Visit
Saline Rinse Pellet
PIV-SLP
F4468.S270
126.PIV.SSP
126
Post Intervention Visit
Stimulated Saliva Pellet
PIV-SSP
Read Taxonomy Assignment - ASV Read Counts by Samples
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[1][2] 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).
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).
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.
Beta diversity compares the similarity (or dissimilarity) of microbial profiles between different
groups of samples. There are many different similarity/dissimilarity metrics.
In general, they can be quantitative (using sequence abundance, e.g., Bray-Curtis or weighted UniFrac)
or binary (considering only presence-absence of sequences, e.g., binary Jaccard or unweighted UniFrac).
They can be even based on phylogeny (e.g., UniFrac metrics) or not (non-UniFrac metrics, such as Bray-Curtis, etc.).
For microbiome studies, species profiles of samples can be compared with the Bray-Curtis dissimilarity,
which is based on the count data type. The pair-wise Bray-Curtis dissimilarity matrix of all samples can then be
subject to either multi-dimensional scaling (MDS, also known as PCoA) or non-metric MDS (NMDS).
MDS/PCoA is a
scaling or ordination method that starts with a matrix of similarities or dissimilarities
between a set of samples and aims to produce a low-dimensional graphical plot of the data
in such a way that distances between points in the plot are close to original dissimilarities.
NMDS is similar to MDS, however it does not use the dissimilarities data, instead it converts them into
the ranks and use these ranks in the calculation.
In our beta diversity analysis, Bray-Curtis dissimilarity matrix was first calculated and then plotted by the PCoA and
NMDS separately. The results are shown below:
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:
Interactive 3D PCoA Plots - Bray-Curtis Dissimilarity
Interactive 3D PCoA Plots - Euclidean Distance
Interactive 3D PCoA Plots - Correlation Coefficients
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 (http://www.compositionaldata.com/).
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. ANCOM transforms the count data into log-ratios and thus is more suitable for comparing the composition of microbiomes in two or more populations
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.
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).
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.
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. Here we use SPIEC-EASI (SParse InversECovariance Estimation
for Ecological Association Inference), a statistical method for the inference of microbial
ecological networks from amplicon sequencing datasets that addresses both of these issues (Kurtz et al., 2015).
SPIEC-EASI combines data transformations developed for compositional data analysis with a graphical model
inference framework that assumes the underlying ecological association network is sparse. SPIEC-EASI provides
two algorithms for network inferencing – 1) Meinshausen-Bühlmann's neighborhood selection (MB method) and inverse covariance selection
(GLASSO method, i.e., graphical least absolute shrinkage and selection operator). This is fundamentally distinct from SparCC, which essentially estimate pairwise correlations. In addition
to these two methods, we provide the results of a third method - SparCC (Sparse Correlations for Compositional Data)(Friedman & Alm 2012), which
is also a method for inferring correlations from compositional data. SparCC estimates the linear Pearson correlations between
the log-transformed components.
References:
Kurtz ZD, Müller CL, Miraldi ER, Littman DR, Blaser MJ, Bonneau RA. Sparse and compositionally robust inference of microbial ecological networks. PLoS Comput Biol. 2015 May 7;11(5):e1004226. doi: 10.1371/journal.pcbi.1004226. PMID: 25950956; PMCID: PMC4423992.
