maurerv / ampliconseq

Process amplicon sequencing data using snakemake

Overview

This pipeline uses the following tools to align paired end amplicon sequencing data:

1. FastQC, to assess sequencing data quality
2. Trim Galore to trim reads using nextera adapters
3. STAR for gapped alignment
4. samtools for alignment statistics and indexing
5. MultiQC to compile everything into a neat report

Configuration

All necessary tools can be installed using conda and the provided environment file as per:

conda env create -f env.yml

The environment specification file does not control the versions of the utilized tools, so its up to the user to keep versions consistent across datasets.

Running the pipeline

Adapting the pipeline to your use cases requires at least two changes to the config.yml. workdir_top is the absolute path to the working directory and STAR_reference specifies the absolute path ot the reference created by the STAR aligner as per the manual.

The working directory needs to contain a folder named 00_fastqc which contains either the fastq files or symbolic links to them. Only files with suffix "_R[1-2].fastq.gz" will be recognized by the pipeline.

Result

After running the pipeline, the working directory will have the following structure

workdir_top
├── 00_fastqc/            # Contains the fastqc analysis of files in 01_fastq_ra
├── 01_fastq_raw/         # Contains the raw fastqs
├── 02_fastq_trimmed/     # Contains the trimmed fastqs
├── 03_star/              # Contains the alignment files from STAR
├── multiqc_data/         # Contains data used by multiqc to generate the final report
├── multiqc_report.html   # Final per sample quality report