Versions follow semantic versioning (
major.minor.patch). Breaking changes
will only occur in major versions with changes noted in this changelog.
pgsc_calc v2.0.0-alpha.3 (2023-10-02)#
Automatically retry scoring with more RAM on larger datasets
Describe scoring precision in docs
Change handling of VCFs to reduce errors when recoding
Internal changes to improve support for custom reference panels
pgsc_calc v2.0.0-alpha.1 (2023-08-11)#
This patch fixes a bug when running the workflow directly from github with the test profile (i.e. without cloning first). Thanks to @staedlern for reporting the problem.
pgsc_calc v2.0.0-alpha (2023-08-08)#
This major release features breaking changes to samplesheet structure to provide more flexible support for extra genomic file types in the future. Two major new features were implemented in this release:
Genetic ancestry group similarity is calculated to a population reference panel (default: 1000 Genomes) when the
--run_ancestryflag is supplied. This runs using PCA and projection implemented in the
Calculated PGS can be adjusted for genetic ancestry using empirical PGS distributions from the most similar reference panel population or continuous PCA-based regressions.
These new features are optional and don’t run in the default workflow. Other features included in the release are:
Speed optimizations for PGS scoring (skipping allele frequency calculation)
pgsc_calc v1.3.2 (2023-01-27)#
This patch fixes a bug that made some PGS Catalog scoring files incompatible with the pipeline. Effect weights were sometimes set to utf-8 strings instead of floating point numbers, which caused an assertion error. Thanks to @j0n-a for reporting the problem.
pgsc_calc v1.3.1 (2023-01-24)#
This patch fixes a bug that breaks the workflow if all variants in one or more PGS scoring files match perfectly with the target genomes. Thanks to @lemieuxl for reporting the problem!
pgsc_calc v1.3.0 (2022-11-21)#
This release is focused on improving scalability.
Variant matching is made more efficient using a split - apply - combine approach when the data is split across chromosomes. This supports parallel PGS calculation for the largest traits (e.g. cancer, 418 PGS [avg 261,000 variants/score) ) in the PGS Catalog on big datasets such as UK Biobank.
Better support for running in offline environments:
Internet access is only required to download scores by ID. Scores can be pre-downloaded using the utils package (https://pypi.org/project/pgscatalog-utils/)
Scoring file metadata is read from headers and displayed in the report (removed API calls during report generation)
Implemented flag (–efo_direct) to return only PGS tagged with exact EFO term (e.g. no PGS for child/descendant terms in the ontology)
pgsc_calc v1.2.0 (2022-10-11)#
This release is focused on improving memory and storage usage.
Allow genotype dosages to be imported from VCF to be specified in
vcf_genotype_fieldof samplesheet (default: GT / hard calls)
Makes use of durable caching when relabelling and recoding target genomes (
Improvements to use less storage space:
All intermediate files are now compressed by default
Add parameter to support zstd compressed input files
Improved memory usage when matching variants (
Revised interface to select scores from the PGS Catalog using flags:
--trait_efo(EFO ID / traits),
--pgp_id(PGP ID / publications),
--pgs_id(PGS ID, individual scores).
pgsc_calc v1.1.0 (2022-09-15)#
The first public release of the pgsc_calc pipeline. This release adds compatibility for every score published in the PGS Catalog. Each scoring file in the PGS Catalog has been processed to provide consistent genomic coordinates in builds GRCh37 and GRCh38. The pipeline has been updated to take advantage of the harmonised scoring files (see PGS Catalog downloads for additional details).
Many of the underlying software tools are now implemented within a
v0.1.2, PGScatalog/pgscatalog_utils and https://pypi.org/project/pgscatalog-utils/ ). The packaging allows for independent testing and development of tools for downloading and working with the scoring files.
The output report has been improved to have more detailed metadata describing the scoring files and how well the variants match the target sampleset(s).
- Improvements to variant matching:
More precise control of variant matching parameters is now possible, like ignoring strand flips
match_variantsshould now use less RAM by default:
A laptop with 16GB of RAM should be able to comfortably calculate scores on the 1000 genomes dataset
Fast matching mode (
--fast_match) is available if ~32GB of RAM is available and you’d like to calculate scores for larger datasets
Groups of scores from the PGS Catalog can be calculated by specifying a specific
--trait(EFO ID) or
--publication(PGP ID), in addition to using individual scoring files
Score validation has been integrated with the test suite
Support for M1 Macs with
--platformparameter (docker executor only)
Implemented a more robust prioritisation procedure if a variant has multiple candidate matches or duplicated IDs
Fixed processing multiple samplesets in parallel (e.g. 1000 Genomes + UK Biobank)
When combining multiple scoring files, all variants are now kept to reflect the correct denominator for % matching statistics.
When trying to correct for strand flips the matched effect allele wasn’t being correctly complemented
pgsc_calc v1.0.0 (2022-05-24)#
This release produces scores that should be biologically meaningful. Significant effort has been made to validate calculate scores on different datasets. In the next release we’ll add score validation to our test suite to make sure calculated scores stay valid in the future.
Add support for PLINK2 format (samplesheet structure changed)
Add support for allosomes (e.g. X, Y)
Improve PGS Catalog compatibility (e.g. missing other allele)
Add automatic liftover of scoring files to match target genome build
Performance improvements to support UK BioBank scale data (500,000 genomes)
Support calculation of multiple scores in parallel
Significantly improved test coverage (> 80%)
Lots of other small changes to improve correctness and handling edge cases
pgsc_calc v0.1.3dev (2022-02-04)#
Simplified JSON input processes
Add first draft of documentation
Add JSON schemas for validating input data (mostly for web platform)
pgsc_calc v0.1.2dev (2022-01-17)#
Add JSON input support for web platform functionality
Set up simple CI tests with Github actions
pgsc_calc v0.1.1dev (2021-12-16)#
First public release
Support applying a single scoring file to target genomic data in GrCh37 build