gaga2 - automated 16S amplicon analysis with Figaro/DADA2

Installation instructions

gaga2 requires a working nextflow installation (v20.4+).

Other dependencies:

• bbmap
• fastqc
• figaro
• R v4+ with dada2, devtools, tidyverse, and cowplot installed

For convenience, gaga2 comes with a Singularity container with all dependencies installed.

singularity pull oras://ghcr.io/zellerlab/gaga2:latest

Usage instructions

Input

gaga2 takes as input Illumina paired-end 16S amplicon sequences (e.g. sequenced on a MiSeq).

Prerequisites

• Read files need to be named according the typical pattern <prefix=sample_id>_R?[12].{fastq,fq,fastq.gz,fq.gz}. They should, but don't have to, be arranged in a sample-based directory structure:

<project_dir> (aka "input_dir")
     |___ <sample_1>
     |        |____ <sample_1_forward_reads>
     |        |____ <sample_2_reverse_reads>
     |
     |___ <sample_2>
     |        |____ <empty samples will be ignored>
     |        
     |___ <sample_n>
              |____ <sample_n_forward_reads>
              |____ <sample_n_reverse_reads>

A flat directory structure (with all read files in the same directory) or a deeply-branched (with read files scattered over multiple levels) should also work.

If gaga2 preprocesses the reads, it will automatically use _R1/2 endings internally.

• If input reads have already been preprocessed, you can set the --preprocessed flag. In this case, gaga2 will do no preprocessing at all and instruct dada2 to perform no trimming. Otherwie, gaga2 will assess the read lengths for uniformity. If read lengths differ within and between samples, preprocessing with figaro is not possible and dada2 will be run without trimming.

• Samples with less than 110 reads after dada2 preprocessing, will be discarded.

Running gaga2

gaga2 can be directly run from github.

nextflow run zellerlab/gaga2 <parameters>

To obtain a newer version, do a

nextflow pull zellerlab/gaga2

before.

In addition, you should obtain a copy of the run.config from the gaga2 github repo and modify it according to your environment.

Mandatory arguments

• --input_dir is the project directory mentioned above.
• --output_dir will be created automatically.
• --amplicon_length this is derived from your experiment parameters (this is not read-length, but the length of the, well, amplicon!)
• --single_end this is only required for single-end libraries (auto-detection of library-type is in progress)

Optional arguments

• --min_overlap of read pairs is 20bp by default
• --primers <comma-separated-list-of-primer-sequences> or --left_primer, and --right_primer If primer sequences are provided via --primers, gaga2 will remove primers and upstream sequences (using bbduk), such as adapters based on the primer sequences. If non-zero primer lengths are provided instead (via --left_primer and --right_primer), figaro will take those into account when determining the best trim positions.
• --preprocessed will prevent any further preprocessing by gaga2 - this flag should only be used if the read data is reliably clean.

internal beta-testing instructions

• The old gaga2 version can be run with source /g/scb2/zeller/schudoma/software/wrappers/gaga2_wrapper before submitting job to cluster
• Please report issues/requests/feedback in the github issue tracker
• If you want to run gaga2 on the cluster, nextflow alone requires >=5GB memory just for 'managing'.