frederic-mahe / Amplicon_Recipes

Recipes for data analysis of amplicon sequencing data

Amplicon recipes

Recipes for data analysis of amplicon sequencing data

Available recipes:

1. 16S rRNA gene amplicon pipeline (16S_pipeline.sh)

1. 16S rRNA gene amplicon pipeline (16S_pipeline.sh)

Data processing pipeline for 16S rRNA gene amplicon raw sequencing data

Dependencies

This pipeline depends on USEARCH and CUTADAPT.
The pipeline has been tested with USEARCH v.10.0.240 and CUTADAPT v.1.9.1.

Installation

1. Clone this repository: git clone https://github.com/SushiLab/Amplicon_Recipes.git
2. Add the 16S_pipeline.sh script to your PATH by modifying your .bashrc file: export PATH="$PATH:<path_to_16S_pipeline.sh>"
3. The pipeline requires USEARCH and CUTADAPT to be executable with the exact commands usearchand cutadapt. You can test that by typing both commands.
   If this does not work, you can add aliases to your .bashrc file. Use a text editor to add the lines alias usearch=<path_to_USEARCH> and alias usearch=<path_to_CUTADAPT> to your .bashrc file and source it: source ~/.bashrc.

Pipeline

The 16S rRNA gene amplicon pipeline processes demultiplexed pair-end fastq files and produces OTU/zOTU abundance tables through the following steps:

1. Merging of pair-end reads.
2. Quality filtering.
3. Primer matching (optional but recommended).
4. Dereplication.
5. OTU clustering with the UPARSE algorithm.
6. zOTU denoting with the UNOISE3 algorithm.
7. Taxonomic annotation of OTUs and zOTUs against SILVA database with LCA approach (optional).
8. Quantification of OTU and zOTU abundances.

Usage

No primer sequences: will skip the primer matching. Only recommended if primer sequences have been already removed and reads trimmed.

16S_pipeline.sh -input_f <input_folder> -output_f <output_folder> -db <path_to_SILVA_database.fasta>

Primer sequences present: will include the primer matching. Recommended if primer sequences have not been yet removed.

16S_pipeline.sh -input_f ./data/ -output_f ./out -db <path_to_SILVA_database.fasta> -primerF <forward_primer> -primerR <reverse_primer> -threads <num_threads>

Example: using SILVA_128_SSURef_Nr99 database and the 515F-Y / 806RB primers for the V4 region:

16S_pipeline.sh -input_f ./data/ -output_f ./out -db SILVA_128_SSURef_Nr99_tax_silva_trunc.fasta -primerF GTGYCAGCMGCCGCGGTAA -primerR ATTAGAWACCCBNGTAGTCC -threads 10

Parameters

Mandatory options:

-input_f Path to input folder with demultiplexed raw reads fastq files. Files must start with the sample identifier. Sample identifier is taken from the FASTQ file name by truncating at the first underscore or period. R1 and R2 files for each sample must have the exact same file name but 'SampleID_R1.fastq' and 'SampleID_R2.fastq'.
-output_f Path to output folder.

General options:

-threads[1-N] Number of threads used (default=1)
-help Show this help

Merging:

-pctid[0-100] Percentage of maximum number of mismatchesas an integer (default=10)
-minoverlap [0-N] Discard pair if alignment is shorter than given value (default=16)

Quality filtering:

-maxee[0-N] Expected errors: discard reads with expected errors > maxee (default=0.1)
-minlength[0-N] Discard sequences with length < minlength (default=100)

Primer match: (skipped if -primerF or primerR options are missing)

-primerF Forward primer with IUPAC wildcard characters.
-primerR Reverse primer with IUPAC wildcard characters (reverse-complement needed).
-minprimfrac[0-1] Minimum fraction of the primer searched by cutadapt (default=1, i.e. the entire primer).
-maxmismatch[1-N] Number of mismatches allowed by cutadapt in each primer (default=0)

Clustering:

-minsize[0-1] Minimum sequence abundance to be considered (default=1, i.e. include singletons)

Taxonomical annotation: (skipped if -db option is missing)

-db Path to database for taxonomical annotation (SILVA db suggested: https://www.arb-silva.de/fileadmin/silva_databases/release_128/Exports/SILVA_128_SSURef_Nr99_tax_silva_trunc.fasta.gz)
-tax_id [0-1] Minimum identity for taxonomic search (default=0.90)

Results

The complete pipeline will produce the following output files:

Report:

report.txt Report of the whole pipeline with basic statistics

Merging:

merged.fq Fastq file with merged reads
merging.log Logfile for the merging step

Filtering:

filtered.fa Fasta file with quality filetered reads
filtered_primermatch.fa Fasta file with reads matchin the primers
filter.log Logfile for the quality filtering step

De-replication:

uniques.fa Fasta file with de-replicated sequences
dereplication.log Logfile for the quality de-replication step

Clustering / Denoising:

otus_uparse.fa Fasta file with OTU representative sequences
otutab_uparse.* OTU table (3 available formats)
clustering.log Logfile for the UPARSE clustering step
make_otutab_uparse.log Logfile for the OTU table quantification step

otus_unoise.fa Fasta file with zOTU sequences
otutab_unoise.* zOTU table (3 available formats)
denoising.log Logfile for the denoising step
make_otutab_unoise.log Logfile for the zOTU table quantification step

Taxonomic annotation:

taxonomy_uparse_lca.txt Taxonomic annotation of OTUs
taxonomy_unoise_lca.txt Taxonomic annotation of zOTUs
taxsearch_uparse.tax All hits to the taxonomic database for OTUs
taxsearch_unoise.tax All hits to the taxonomic database for zOTUs
taxsearch_uparse.log Logfile for the OTU taxonomic annotation step
taxsearch_unoise.log Logfile for the zOTU taxonomic annotation step