nf-core/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.
Introduction
This document describes the output produced by the pipeline. Most of the plots are taken from the MultiQC report, which summarises results at the end of the pipeline.
The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.
Pipeline overview
The pipeline is built using Nextflow and processes data using the following steps:
- FastQC - Raw read QC
- MultiQC - Aggregate report describing results and QC from the whole pipeline
- Pipeline information - Report metrics generated during the workflow execution
- Expression Atlas: get Expression Atlas accessions and download data
- Normalisation: normalise raw data (with DESeq2 or EdgeR)
- gProfiler: map gene IDS to Ensembl IDS
- Gene Statistics: merge all counts, compute gene variation statistics and get the most stable genes
Output files
FastQC
Output files
fastqc/
*_fastqc.html
: FastQC report containing quality metrics.*_fastqc.zip
: Zip archive containing the FastQC report, tab-delimited data file and plot images.
FastQC gives general quality metrics about your sequenced reads. It provides information about the quality score distribution across your reads, per base sequence content (%A/T/G/C), adapter contamination and overrepresented sequences. For further reading and documentation see the FastQC help pages.
MultiQC
Output files
multiqc/
- MultiQC report file:
multiqc_report.html
. - MultiQC data dir:
multiqc_data
. - Plots created by MultiQC:
multiqc_plots
.
- MultiQC report file:
MultiQC](http://multiqc.info) is a visualization tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available in the report data directory.
Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see http://multiqc.info.
Gene Variation
Output files
gene_variation/
- A list of the most stable genes in
stats_most_stable_genes.csv
. - Descriptive statistics for all genes in
stats_all_genes.csv
- All normalised counts (for each gene and each sample) in
count_summary.csv
.
- A list of the most stable genes in
Expression Atlas
Output files
expressionatlas/
- List of accessions found when querying Expression Atlas:
accessions.txt
. - List of count datasets (normalized:
*.normalised.csv
/ raw:*.raw.csv
) and experimental designs (*.design.csv
) downloaded from Expression Atlas.
- List of accessions found when querying Expression Atlas:
Normalisation
Output files
List of newly normalised datasets in normalisation/
normalisation/deseq2/
for DESeq2normalisation/edger/
for EdgeR
GProfiler IDMapping
Output files
idmapping/
- Count datasets whose gene IDs have been mapped to Ensembl IDs:
*_renamed.csv
. - Table associating original gene IDs and Ensembl IDs:
*_mapping.csv
. - Ensembl gene metadata (name and description):
*_metadata.csv
.
- Count datasets whose gene IDs have been mapped to Ensembl IDs:
Pipeline information
Output files
pipeline_info/
- Reports generated by Nextflow:
execution_report.html
,execution_timeline.html
,execution_trace.txt
andpipeline_dag.dot
/pipeline_dag.svg
. - Reports generated by the pipeline:
pipeline_report.html
,pipeline_report.txt
andsoftware_versions.yml
. Thepipeline_report*
files will only be present if the--email
/--email_on_fail
parameter’s are used when running the pipeline. - Parameters used by the pipeline run:
params.json
.
- Reports generated by Nextflow:
Nextflow provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.