dalmolingroup/bulkrna is an analysis pipeline for pre-processing, alignment and quantification of bulk RNA-Seq data.
The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from nf-core/modules in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!
- Read QC (
FastQC
) - Read trimming (
fastp
) - Alignment and quantification (
kallisto
) - Import quantifications into a count matrix, at gene and transcript level(
tximport
) - Present QC for trimmed reads and alignment (
MultiQC
)
-
Install
Nextflow
(>=22.10.1
) -
Install any of
Docker
,Singularity
(you can follow this tutorial),Podman
,Shifter
orCharliecloud
for full pipeline reproducibility (you can useConda
both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see docs). -
Download the pipeline and test it on a minimal dataset with a single command:
nextflow run dalmolingroup/bulkrna -profile test,YOURPROFILE --outdir <OUTDIR>
For example, run the test with Docker:
nextflow run dalmolingroup/bulkrna -profile test,docker --outdir bulkrna_results
Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (YOURPROFILE
in the example command above). You can chain multiple config profiles in a comma-separated string.
- The pipeline comes with config profiles called
docker
,singularity
,podman
,shifter
,charliecloud
andconda
which instruct the pipeline to use the named tool for software management. For example,-profile test,docker
. - Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use
-profile <institute>
in your command. This will enable eitherdocker
orsingularity
and set the appropriate execution settings for your local compute environment. - If you are using
singularity
, please use thenf-core download
command to download images first, before running the pipeline. Setting theNXF_SINGULARITY_CACHEDIR
orsingularity.cacheDir
Nextflow options enables you to store and re-use the images from a central location for future pipeline runs. - If you are using
conda
, it is highly recommended to use theNXF_CONDA_CACHEDIR
orconda.cacheDir
settings to store the environments in a central location for future pipeline runs.
- Start running your own analysis!
nextflow run dalmolingroup/bulkrna --input samplesheet.csv --outdir <OUTDIR> --transcriptome <PATH TO TRANSCRIPTOME FASTA> --gtf <PATH TO GTF FILE> -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>
To acquire reference transcriptome and GTF files to use in your execution, we recommend using the Ensembl database.
dalmolingroup/bulkrna was originally written by João Cavalcante.
If you would like to contribute to this pipeline, please see the contributing guidelines.
An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md
file.
This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.
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.