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stableexpression

Pipeline dedicated to finding the most stable genes among a single or multiple expression dataset(s). It is useful in particular for finding the most suitable RT-qPCR reference genes for a specific species.

https://github.com/nf-core/stableexpression

Science Score: 57.0%

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    Found 10 DOI reference(s) in README
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    Low similarity (11.9%) to scientific vocabulary

Keywords

expression housekeeping-genes nextflow nf-core qpcr-analysis workflow
Last synced: 6 months ago · JSON representation ·

Repository

Pipeline dedicated to finding the most stable genes among a single or multiple expression dataset(s). It is useful in particular for finding the most suitable RT-qPCR reference genes for a specific species.

Basic Info
Statistics
  • Stars: 4
  • Watchers: 231
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Topics
expression housekeeping-genes nextflow nf-core qpcr-analysis workflow
Created about 1 year ago · Last pushed 9 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

nf-core/stableexpression

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Introduction

nf-core/stableexpression is a bioinformatics pipeline that aims at finding the most stable genes among a single or multiple public / local count datasets. It takes as input a species name (mandatory), keywords for expression atlas search (optional) and / or a CSV input file listing local raw / normalised count datasets (optional). A typical usage is to find the most suitable qPCR housekeeping genes for a specific species (and optionally specific conditions).

Pipeline summary

  1. Get Expression Atlas accessions corresponding to the provided species (and optionally keywords) (Expression Atlas; optional)
  2. Download Expression Atlas data (Expression Atlas; optional)
  3. Normalize raw data (using DESeq2 or EdgeR)
  4. Map gene IDS to Ensembl IDS for standardisation among datasets (g:Profiler)
  5. Compute pairwise gene variation
  6. Compute gene variation statistics and get the most stable genes
  7. 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 listing the different count datasets:

datasets.csv:

csv counts,design,normalised path/to/normalised.counts.csv,path/to/normalised.design.csv,true path/to/raw.counts.csv,path/to/raw.design.csv,false

Make sure to format your datasets properly:

counts.csv:

csv ,sample_A,sample_B,sample_C gene_1,1,2,3 gene_2,1,2,3 ...

design.csv:

csv sample,condition sample_A,condition_1 sample_B,condition_2 ...

Now you can run the pipeline as follows:

bash nextflow run nf-core/stableexpression \ -profile docker \ --species <SPECIES> \ --eatlas_accessions <ACCESSIONS> \ --eatlas_keywords <KEYWORDS> \ --datasets ./datasets.csv \ --outdir ./results

[!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/stableexpression was originally written by Olivier Coen.

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 #stableexpression 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.

Owner

  • Name: nf-core
  • Login: nf-core
  • Kind: organization
  • Email: core@nf-co.re

A community effort to collect a curated set of analysis pipelines built using Nextflow.

Citation (CITATIONS.md) 

# nf-core/stableexpression: Citations

## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/)

> Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031.

## [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/)

> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311.

## Pipeline tools

- [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)

> Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online].

- [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/)

> Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924.

- [Expression Atlas](https://www.ebi.ac.uk/gxa/home)

> Papatheodorou I, Fonseca NA, Keays M, Tang YA, Barrera E, Bazant W, Burke M, Füllgrabe A, Muñoz-Pomer Fuentes A, George N, Huerta L, Koskinen S, Mohammed S, Geniza M, Preece J, Jaiswal P, Jarnuczak AF, Huber W, Stegle O, Vizcaino JA, Brazma A, Petryszak R. Expression Atlas: gene and protein expression across multiple studies and organisms. Nucleic Acids Res. 2017 Nov 20;46(Database issue):D246–D251. doi: 10.1093/nar/gkx1158. PubMed PMID: 29165655.

- [g:Profiler](https://biit.cs.ut.ee/gprofiler/gost)

> Reimand J, Kull M, Peterson H, Hansen J, Vilo J. g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res. 2007 May 3;35(Web Server issue):W193–W200. doi:10.1093/nar/gkm226. PubMed PMID: 17478515.

- [DESeq2](https://bioconductor.org/packages/release/bioc/html/DESeq2.html)

> Love MI, Huber W & Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology. 2014;15(12):550. doi: 10.1186/s13059-014-0550-8. PubMed PMID: 25516281.

## [EdgeR](https://bioconductor.org/packages/release/bioc/html/edgeR.html)

> Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010 Jan 1;26(1):139-40. doi: 10.1093/bioinformatics/btp616. Pubmed PMID: 19910308.

## Software packaging/containerisation tools

- [Anaconda](https://anaconda.com)

  > Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.

- [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/)

  > Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.

- [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/)

  > da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671.

- [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241)

  > Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. doi: 10.5555/2600239.2600241.

- [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/)

  > Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675.

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Last synced: 6 months ago

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Dependencies

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