Workflow summary#

The workflow performs the following steps:

• Downloading scoring files using the PGS Catalog API in a specified genome build (GRCh37 and GRCh38).

• Reading custom scoring files (and performing a liftover if genotyping data is in a different build).

• Automatically combines and creates scoring files for efficient parallelcomputation of multiple PGS.

• Matches variants in the scoring files against variants in the target dataset (in plink bfile/pfile or VCF format).

• Calculates PGS for all samples (linear sum of weights and dosages).

• Creates a summary report to visualize score distributions and pipeline metadata (variant matching QC).

And optionally has additional functionality to:

• Use a reference panel to obtain genetic ancestry data using PCA, and define the most similar population in thereference panel for each target sample.

• Report PGS using methods to adjust for genetic ancestry.

SeeFeatures under development section for information about planned updates.

The workflow relies on open source scientific software, including:

• PLINK 2

• PGS Catalog Utilities

• FRAPOSA

A full description of included software is described inReference: container images.

Quick example#

1. InstallNextflow

2. InstallDocker orSingularity (minimumv3.8.3) for fullreproducibility orConda as a fallback

3. Calculate some polygenic scores using synthetic test data:

$nextflowrunpgscatalog/pgsc_calc-profiletest,docker

The workflow should output:

... <configuration messages intentionally not shown> ...------------------------------------------------------If you use pgscatalog/pgsc_calc for your analysis please cite:* The Polygenic Score Catalog  https://doi.org/10.1038/s41588-021-00783-5* The nf-core framework  https://doi.org/10.1038/s41587-020-0439-x* Software dependencies  https://github.com/pgscatalog/pgsc_calc/blob/master/CITATIONS.md------------------------------------------------------executor >  local (7)[49/d28766] process > PGSC_CALC:PGSCALC:INPUT_CHECK:SAMPLESHEET_JSON (samplesheet.csv)           [100%] 1 of 1 ✔[c3/a8e0d9] process > PGSC_CALC:PGSCALC:INPUT_CHECK:SCOREFILE_CHECK                              [100%] 1 of 1 ✔[-        ] process > PGSC_CALC:PGSCALC:MAKE_COMPATIBLE:PLINK2_VCF                               -[7c/5cca6c] process > PGSC_CALC:PGSCALC:MAKE_COMPATIBLE:PLINK2_BFILE (cineca_synthetic_subset)   [100%] 1 of 1 ✔[3b/ce0e39] process > PGSC_CALC:PGSCALC:MAKE_COMPATIBLE:MATCH_VARIANTS (cineca_synthetic_subset) [100%] 1 of 1 ✔[2e/fb3233] process > PGSC_CALC:PGSCALC:APPLY_SCORE:PLINK2_SCORE (cineca_synthetic_subset)       [100%] 1 of 1 ✔[b5/fc5b1e] process > PGSC_CALC:PGSCALC:APPLY_SCORE:SCORE_REPORT (1)                             [100%] 1 of 1 ✔[03/009cb6] process > PGSC_CALC:PGSCALC:DUMPSOFTWAREVERSIONS (1)                                 [100%] 1 of 1 ✔-[pgscatalog/pgsc_calc] Pipeline completed successfully-

If you want to try the workflow with your own data, have a look at theGetting started section.

Documentation#

• Get started: install pgsc_calc and calculate some polygenic scores quickly

• How-to guides: step-by-step guides, covering different use cases

• Reference guides: technical information about workflow configuration

• Explanations: more detailed explanations about PGS calculation and results

Changelog#

TheChangelog page describes fixes and enhancements for each version.

Features under development#

These are some of the fetures and improvements we’re planning for thepgsc_calc:

• Further optimizations to the PCA & ancestry similarity analysis steps focused on improving automatic QC

• Performance improvements to makepgsc_calc work with 1000s of scoring files in paralell (e.g. integrationwithOmicsPred)

Credits#

pgscatalog/pgsc_calc is developed as part of the PGS Catalog project, acollaboration between the University of Cambridge’s Department of Public Healthand Primary Care (Michael Inouye, Samuel Lambert) and the EuropeanBioinformatics Institute (Helen Parkinson, Laura Harris).

The pipeline seeks to provide a standardized workflow for PGS calculation andancestry inference implemented in nextflow derived from an existing set oftools/scripts developed by Inouye lab (Rodrigo Canovas, Scott Ritchie, JingqinWu) and PGS Catalog teams (Samuel Lambert, Laurent Gil).

The adaptation of the codebase, nextflow implementation, and PGS Catalog featuresare written by Benjamin Wingfield, Samuel Lambert, Laurent Gil with additional inputfrom Aoife McMahon (EBI). Development of new features, testing, and code reviewis ongoing including Inouye lab members (Rodrigo Canovas, Scott Ritchie) and others. Amanuscript describing the tool is in preparation (seeCitations) and wewelcome ongoing community feedback before then via ourdiscussion board orissue tracker.