nf-core/callingcards
A pipeline for processing calling cards data
Introduction
*nf-core/callingcards* is a bioinformatics pipeline that ...
*nf-core/callingcards* is a bioinformatics best-practice analysis pipeline for An automated processing pipeline for mammalian bulk calling cards experiments.
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 which makes installation trivial and results reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which simplifies maintenance and software updates. 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.
On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources. The results obtained from the full-sized test can be viewed on the nf-core website.
Pipeline summary
- Prepare Reads
- Extract barcodes (
UMItools
) - Trim, and reduce to only R1 depending on user input (
Trimmomatic
)
- Extract barcodes (
- Read QC (
FastQC
) - Prepare the Genome
- Samtools faidx and aligner indicies
- Alignment
- Process Alignments
- Extract alignment QC metrics ([
Samtools
](https://www.htslib.org/, Picard, RSeQC) - Quantify transposon hops and perform calling cards specific QC (pycallingcards)
- Peak calling and significance statistics (pycallingcards)
- Extract alignment QC metrics ([
- Present QC for raw read and alignment metrics (
MultiQC
) - Prepare the Genome
- Samtools faidx and aligner indicies
- Alignment
- Process Alignments
- Extract alignment QC metrics ([
Samtools
](https://www.htslib.org/, Picard, RSeQC) - Quantify transposon hops and perform calling cards specific QC (pycallingcards)
- Peak calling and significance statistics (pycallingcards)
- Extract alignment QC metrics ([
- Present QC for raw read and alignment metrics (
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.
Note that more detailed instructions are available in usage.
-
Install
Nextflow
(>=22.10.1
) -
Install any of
Docker
,Singularity
(you can follow this tutorial),Podman
,Shifter
orCharliecloud
for full pipeline reproducibility.
-
Testing with a minimal data set. This tests the installation only.
nextflow run nf-core/callingcards -profile test,YOURPROFILE --outdir <OUTDIR>
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 (
test_human
andsingularity
in the example command above). You can chain multiple config profiles in a comma-separated string, as demonstrated.*Note*: this pipeline is not currently configured to run with conda.
-->
-
Start running your own analysis!
nextflow run nf-core/callingcards \ -params-file params.json \ -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> \ # possibly more config settings for your environment -c local.config
The params.json
file is described in usage
Configuration is discussed in Pipeline configuration and
in the configuration section of the nextflow documentation
Documentation
To see the the results of a 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/callingcards is implemented in nextflow by Chase Mateusiak. It was adapted from scripts written by:
- Rob Mitra
- Juanru Guo
nf-core/callingcards is implemented in nextflow by Chase Mateusiak. It was adapted from scripts written by: - Rob Mitra
- Juanru Guo
We thank the following people for their extensive assistance in the development of this pipeline:
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 #callingcards
channel (you can join with this invite).
Citations
<!-- TODO nf-core: Add citation for pipeline after first release. Uncomment lines below and update Zenodo doi and badge at the top of this file. --> <!-- If you use nf-core/callingcards for your analysis, please cite it using the following doi: [10.5281/zenodo.XXXXXX](https://doi.org/10.5281/zenodo.XXXXXX) -->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.