Skip to content

Latest commit

 

History

History
99 lines (66 loc) · 6.41 KB

README.md

File metadata and controls

99 lines (66 loc) · 6.41 KB

nf-core/fastqrepair

GitHub Actions CI Status GitHub Actions Linting StatusAWS CICite with Zenodo nf-test

Nextflow run with conda run with docker

Launch on Seqera Platform

Get help on SlackFollow on TwitterFollow on MastodonWatch on YouTube

Introduction

nf-core/fastqrepair is a bioinformatics pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, and settles reads that became disordered. It takes a samplesheet and FASTQ/FASTQ.gz files as input (both single-end and paired-end) and produces clean FASTQ files and a QC report.

pipeline_diagram

  1. Recover reads from corrupted fastq.gz file (gzrt)
  2. Make recovered reads well-formed (fastqwiper)
  3. Drop unpaired reads (trimmomatic)
  4. Re-pair reads (bbmap/repair.sh)

Usage

Note

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

sample,fastq_1,fastq_2
mysampleA,sample_R1.fastq.gz,sample_R2.fastq.gz
mysampleB,sample_R3.fastq.gz,sample_R4.fastq.gz
mysampleC,sample_R5.fastq.gz

Each row represents a fastq file (single-end) or a pair of fastq files (paired end). Rows with the same sample identifier are not allowed. Row with different sample identifiers but same file names are not allowed.

Now, you can run the pipeline using:

nextflow run nf-core/fastqrepair \
   -profile <test/docker/singularity/.../institute> \
   --input samplesheet.csv \
   --outdir <OUTDIR>

Warning

Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

This pipeline produces clean and well-formed fastq files together with short textual reports of the cleaning actions.

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Credits

nf-core/fastqrepair was designed and written by Tommaso Mazza.

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on the Slack #fastqrepair channel (you can join with this invite).

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.