Workflow for processing phenotypic information from CB.
The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.
-
Install
nextflow
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Install either
Docker
orSingularity
for full pipeline reproducibility (please only useConda
as a last resort; see docs) -
Download the pipeline and test it on a minimal dataset with a single command:
nextflow run lifebit-ai/phenowrangle -profile plink_binary
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Start running your own analysis!
nextflow run main.nf --mode "plink" \ --pheno_data "s3://lifebit-featured-datasets/pipelines/biobank-gwas/cohort_data_phenos.csv" \ --pheno_metadata "s3://lifebit-featured-datasets/pipelines/biobank-gwas/metadata.csv" \ --continuous_var_aggregation "mean" \ --continuous_var_transformation "zscore" \ --pheno_col "Specimen type" \ --design_mode 'case_vs_control_contrast' \ --case_group "NOSE" \ --trait_type "binary" \
See usage docs for all of the available options when running the pipeline.
The lifebit-ai/phenowrangle pipeline comes with documentation about the pipeline which you can read at https://lifebit-ai/phenowrangle/docs or find in the docs/
directory.
lifebit-ai/phenowrangle
was originally written by Marcos Cámara Donoso & Christina Chatzipantsiou.
If you would like to contribute to this pipeline, please see the contributing guidelines.
NOTE: This pipeline was created using the nf-core template. For further information or help with nf-core pipelines, you can get in touch with the core developers and community on Slack (you can join with this invite).
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. ReadCube: Full Access Link