nf-core/crispriscreen is a bioinformatics best-practice analysis pipeline to process next generation sequencing data obtained from CRISPRi repression library screenings.
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!
- Sub-sampling of reads (
Seqtk/sample
, optional) - Read QC (
FastQC
) - Generic adapter and quality trimming (
Trim Galore!
) - Specific primer sequence trimming (
cutadapt
) - Preparation of
*.fasta
library (customR
script) - Alignment using (
Bowtie2
)- Build index from
*.fasta
library - Align reads to library
- Optional filtering by mapping quality
- Build index from
- Count reads per target and input file (
subread/featurecounts
) - Quantify gene fitness score from multiple targets per gene
- Option 1: Gene fitness is calculated using
Mageck
MLE - Option 2: Gene fitness is calculated using
DESeq2
- Option 1: Gene fitness is calculated using
- Generate HTML report with fitness results (
R markdown
) - Present QC for raw and mapped reads (
MultiQC
)
-
Install
Nextflow
(>=23.04.0
). It is recommended to useConda
(ormamba
/micromamba
) to install all dependencies in a fresh environment.conda create --name env_nf conda activate env_nf conda install -c conda-forge nextflow
-
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).conda install -c conda-forge singularity
-
Download the pipeline.
cd <your/target/dir> git clone https://github.com/MPUSP/nf-core-crispriscreen
-
Test it on the minimal dataset included with this repository. Since
nf-core-crispriscreen
is not a canonicalnf-core
pipeline (yet), it is necessary to indicate the path to the pipeline folder after therun
statement.The generalized command to run the pipeline:
nextflow run <path/to/nf-core-crispriscreen> -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> --input <sample_sheet> --fasta <fasta_file> --outdir <path/to/output>
The command to run the pipeline on the enclosed test data using
Singularity
(recommended):cd path/to/nf-core-crispriscreen nextflow run ./ -profile singularity --input "assets/samplesheet.csv" --fasta "assets/library.fasta" --outdir "results"
- 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.
- The pipeline comes with config profiles called
The nf-core/crispriscreen pipeline comes with documentation about the pipeline usage and output.
The following people contributed to the nf-core/crispriscreen pipeline:
- Dr. Michael Jahn, MPUSP Berlin (ORCID) - main author and maintainer
- Dr. Ute Hoffmann, Science for Life Lab, Stockholm - contributor
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 #crispriscreen
channel (you can join with this invite).
The following scientific articles are related to this pipeline.
The new version of CRISPRi libary for which this Nextflow pipeline was developed:
Rui Miao, Michael Jahn, Kiyan Shabestary, Elton Paul Hudson. CRISPR interference screens reveal tradeoffs between growth rate and robustness in Synechocystis sp. PCC 6803 across trophic conditions bioRxiv 2023.02.13.528328. https://doi.org/10.1101/2023.02.13.528328
The original publication of the CRISPRi library for which a precursor of this pipeline was developed:
Lun Yao, Kiyan Shabestary, Sarah Björk, Johannes Asplund-Samuelsson, Hakan Joensson, Michael Jahn & Elton Paul Hudson. Pooled CRISPRi screening of the cyanobacterium Synechocystis sp PCC 6803 for enhanced industrial phenotypes. Nature Communications, 11 (1666), 1–13. 2020. https://doi.org/10.1101/823534
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.