mpozuelo / exome_mosdepth

Mosdepth and python scripts to get the coverage of exams

Introduction

mpozuelo/MGI_demux is a bioinformatics analysis pipeline used for demultiplexing Illumina data with i5 and i7 of.

The workflow processes raw data from FastQ inputs (FastQC, cutadapt) for demultiplexing See the output documentation for more details of the results.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

Quick Start

i. Install nextflow

ii. Install one of docker, singularity or conda

iii. Start running your own analysis!

You need to organize your fastq files as follows 'working_directory/data/fastq/run_id/lane/run_id_lane_read{1,2}.fq.gz'. Then from the working directory run the following instruction.

nextflow run mpozuelo/MGI_demux -profile <docker/singularity/conda> --input 'samplesheet.txt'

The samplesheet used must have at least 6 columns WITHOUT header: sample_ID, index_sequence, index2_sequence, barcode_sequence, run_ID, lane

See usage docs for all of the available options when running the pipeline.

Documentation

The mpozuelo/MGI_demux pipeline comes with documentation about the pipeline, found in the docs/ directory:

1. Running the pipeline

Credits

These scripts were originally written for demultiplexing Illumina data with i5 and i7 adapters by Marta Pozuelo (@mpozuelo)