A rápido and lightweight method to compute Polygenic Risk Scores.
Last update: 2022-06-15
Current version: 2.2.0.9000
This package allows to quickly (rápido is Spanish for “fast”) compute polygenic scores (PGS) from case-control or quantitative trait GWAS summary statistic datasets, without the need of an external validation dataset.
You can find a description of the ideas behind RápidoPGS, as well as technical details in our Bioinformatics paper:
rapidopgs_multi()
, which now allows users to use their own
LD matrices instead of computing them on the go from a reference panel.
For European datasets, we recommend downloading UK Biobank LD matrices
kindly provided by Privé et al., which can be accessed here.rapidopgs_multi()
is not supplied input of data.table
class, and removed a deprecated argument in runsusie()
internal function that was preventing rapidopgs_multi()
to
run properly.runsusie()
in rapidopgs_multi()
that used to supply an extra zero element which is not supplied
anymore.rapidopgs_multi()
, which is no longer required.RápidoPGS (2.1.0) is now available on CRAN. You can install it by typing the code below.
install.packages("RapidoPGS")
There’s also a development version, that can be installed from GitHub.
library(remotes)
install_github('GRealesM/RapidoPGS')
RápidoPGS has some dependencies that aren’t available directly from CRAN, so must be installed a bit differently.
GenomicRanges
GenomicRanges
package is a Bioconductor package. Please
type:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GenomicRanges")
Full documentation and vignettes are available on the website (click on the cat if you’re at the GitHub repo).