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16S tutorial

Vikash Singh
November 14, 2021
reference: https://github.com/LangilleLab/microbiome_helper/wiki/Amplicon-SOP-v2-(qiime2-2019.10)
reference: https://docs.qiime2.org/2019.10/tutorials/

1 data preparation

1.0.1 copy/transfer all the fastq.gz files to fastq_files dir

mkdir fastq_files

1.0.2 make manifest file

job_manifest.tsv tab-separated values (TSV) file
ref: https://github.com/qiime2/docs/blob/master/source/tutorials/importing.rst#fastq-manifest-formats
sample-id   forward-absolute-filepath   reverse-absolute-filepath
Con5090Ileum    $PWD/fqgz/1183-1_S1_L001_R1_001.fastq.gz    $PWD/fqgz/1183-1_S1_L001_R2_001.fastq.gz
Con8124Ileum    $PWD/fqgz/1183-19_S19_L001_R1_001.fastq.gz  $PWD/fqgz/1183-19_S19_L001_R2_001.fastq.gz
...

1.0.3 make metadata file

for whole job
job_meta.tsv tab-separated values (TSV) file
ref: https://docs.qiime2.org/2019.10/tutorials/metadata/
sample-id   GroupID treatment-group E.coliChallenge Sex Euth    PigID   Sourceofsample  Datetaken   NGS-SampleNo
#q2:types   categorical categorical categorical categorical categorical categorical categorical categorical categorical
Con5090Ileum    C   Control NO  M   1   5090    Ileum   1/7/2019    1
Con8124Ileum    C   Control NO  F   2   8124    Ileum   5/7/2019    19
Con8141Ileum    C   Control NO  M   2   8141    Ileum   5/7/2019    20
...
for categorical variables
e.g.GroupID tab-separated values (TSV) file
sample-id   GroupID
#q2:types   categorical
C   C
CR  CR
CR-EC   CR-EC
EC  EC

1.0.4 prepare/download database for taxonomy assignment

We use SILVA database silva_132_99_V4/silva-132-99-515-806-nb-classifier.qza

2 QIIME2 anlysis steps

2.1 data importing

reads type" PairedEndFastqManifestPhred33V2
code in qiime2:
qiime tools import \
  --type 'SampleData[PairedEndSequencesWithQuality]' \
  --input-path job_manifest.tsv \
  --output-path paired-end-demux.qza \
  --input-format PairedEndFastqManifestPhred33V2

the above code produces the paired-end-demux.qza file

2.2 primer trimming with cutadapt

ref https://github.com/SchlossLab/MiSeq_WetLab_SOP
DNA was amplified by using the 515f/806r primer set:
Forward V4: GTGCCAGCMGCCGCGGTAA
Reverse V4: GGACTACHVGGGTWTCTAAT

code in qiime2:

qiime cutadapt trim-paired \
   --i-demultiplexed-sequences paired-end-demux.qza \
   --p-cores 20 \
   --p-front-f GTGCCAGCMGCCGCGGTAA \
   --p-front-r GGACTACHVGGGTWTCTAAT \
   --o-trimmed-sequences pe_reads_cutadapt_trimmed.qza \
   --verbose \
   &> primer_trim.log

--p-cores is number of cores. the above code produces the pe_reads_cutadapt_trimmed.qza file.

2.3 Summarize trimmed FASTQs

  • Check quality plots and sequence length
    • code in qiime2:
qiime demux summarize \
    --i-data pe_reads_cutadapt_trimmed.qza \
    --o-visualization pe_reads_cutadapt_trimmed.qzv
To view and check the pe_reads_cutadapt_trimmed.qzv, you can

Based on the plots you see in qzv, decide values would you choose for --p-trunc-len and --p-trim-left in DADA2 denoising ref: https://docs.qiime2.org/2019.10/tutorials/atacama-soils/