Giter VIP home page Giter VIP logo

createpanelrefs's Introduction

nf-core/createpanelrefs

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

Nextflow run with conda run with docker run with singularity Launch on Seqera Platform

Get help on Slack Follow on Twitter Follow on Mastodon Watch on YouTube

Introduction

nf-core/createpanelrefs is a bioinformatics helper pipeline that will help in creating panel of normals and other models.

  1. Read QC (FastQC)
  2. Build Panel of Normals for CNVKIT
  3. Build ploidy and cnv calling models for GATK's germlinecnvcaller workflow
  4. Build Panel of Normals for GENS
  5. Build Panel of Normals for Mutect2
  6. Present QC for raw reads (MultiQC)

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,bam,bai,cram,crai
sample1,sample1.bam,sample1.bai,,
sample2,sample2.bam,,,
sample3,sample3.bam,sample3.bai,,
sample4,sample4.bam,,,

Each row in the samplesheet represents an alignment file, and it is important that you provide the files in the right format for the analysis you want to run.

Tool Alignment format
cnvkit bam
germlinecnvcaller bam or cram or a mix of both

Now, you can run the pipeline using:

nextflow run nf-core/createpanelrefs \
   -profile <docker/singularity/.../institute> \
   --input samplesheet.csv \
   --tools <cnvkit/germlinecnvcaller> \
   --genome GATK.GRCh38 \
   --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

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/createpanelrefs was originally written by @maxulysse. @marrip contributed in the idea that started it all. @matthdsm and @FriederikeHanssen contributed in the actual design. @ramprasadn's interest was the final push that led to the creation.

We thank the following people for their extensive assistance in the development of this pipeline:

  • @jfy133
  • @JoseEspinosa

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 #createpanelrefs 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.

createpanelrefs's People

Contributors

lescai avatar maxulysse avatar nf-core-bot avatar ramprasadn avatar

Stargazers

 avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

createpanelrefs's Issues

pipeline does not generate cnv models

Description of the bug

The pipeline ends with error with ~120 samples:
A USER ERROR has occurred: Bad input: Filtering removed all intervals. Select less strict filtering criteria.

However it does not generate cnv model or ploidy (a run in cohort mode with the samples provided). Only readcounts are available in folder readcounts (hdf5 format).

Command used and terminal output

nextflow run /playground/nf-core-createpanelrefs_dev/dev \
   -profile singularity \
   --input /playground/dataset_cnvs/samplesheets_sarek/samplesheet_bams_illumina.csv \
   --tools germlinecnvcaller \
   --fasta /corebm/tmp/bams/hg38.fa --dict /corebm/tmp/bams/hg38.dict --fai /corebm/tmp/bams/hg38.fa.fai \
   --outdir /playground/dataset_cnvs/germlinecnvcaller_illumina_reference_nochrM \
   --ploidy_priors /playground/dataset_cnvs/priors.table \
   --padding 250 \
   --bin_length 0 \
   --mappable_regions /playground/dataset_cnvs/Illumina-truseq-rapid-exome_v1.2_hg38_target_orig_nochrM.bed

Relevant files

next.log

System information

nextflow version 23.10.1.5891
Workstation
local executor
singularity
ubuntu 22.04
nf-core/createpanelrefs dev (22/01/2024)

Add igenomes support

          This section made me realize that we are using getGenomeAttribute from the utils subworkflow in this pipeline. We should change that in another (next?) PR.

Originally posted by @ramprasadn in #8 (comment)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.