Awesome

Assembly

Whole genome de-novo assembly using velvet

Quick Start

To execute the pipeline on your computer, first pull the docker image

docker pull hadrieng/simple_assembly

Then execute the workflow

nextflow run assembly.nf

It will produce a contig fasta file for the sample data present in this directory.

Pipeline Parameters

--reads

• Specifies the location of the reads gzipped fastq file
• By default it is set to data/ERR486840_1.fastq.gz

--mode

• Specifies the mode for running the pipeline
• It must be ion or illumina
• If set ion, non adapter trimming will be performed
• If set to illumina, see option --adapt below

--adapt

• Optional. It is used by --mode illumina
• Specifies the location of the adapters file for adapter trimming
• It must end in .fasta
• By default it is set to data/adapters.fasta

Profiles

The SGBC cluster uses a module system. Pulling the docker image is not required!

By default, the pipeline runs locally using docker. If you run the nonpareil pipeline on the SGBC cluster, please pass the option -profile planet

Example:

nextflow run nonpareil.nf -profile planet --reads /proj/my_proj/data/reads.fastq --mode illumina --adapt custom_adapters.fasta

Citations

If you use this pipeline in your research, please cite:

• Buffalo Vince (2011), Scythe: A Bayesian adapter trimmer [Software]. Available at https://github.com/vsbuffalo/scythe
• Joshi NA, Fass JN. (2011). Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files [Software].Available at https://github.com/najoshi/sickle.
• D.R. Zerbino and E. Birney (2008), Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Research, 18: 821-829