The goal of flashfm is to use GWAS summary statistics to jointly fine-map genetic associations for several related quantitative traits in a Bayesian framework that leverages information between the traits.
Website available at: https://jennasimit.github.io/flashfm/.
Details available in https://rdcu.be/czYpf .
Hernandez, N., Soenksen, J., Newcombe, P., Sandhu, M., Barroso, I., Wallace, C., Asimit, J. The flashfm approach for fine-mapping multiple quantitative traits. Nat Commun 12, 6147 (2021). https://doi.org/10.1038/s41467-021-26364-y
Flashfm could be installed with ease on versions of R > 3.6.0. If installing on a Windows machine, Rtools must be installed. Installation time is estimated as 2 minutes.
# install.packages("devtools")
devtools::install_github("jennasimit/flashfm")
The following packages from CRAN and Bioconductor are required:
install.packages("Rcpp")
install.packages("RcppArmadillo")
install.packages("parallel")
install.packages("data.table")
install.packages("gtools")
install.packages("rlist")
install.packages("MASS")
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("snpStats")
as well as the following dependencies from GitHUb
# install and load R2BGLiMS
remotes::install_github("pjnewcombe/R2BGLiMS")
NB: Must have a Java JDK installed in order to install and run R2BGLiMS. This is only needed if you need to run single-trait fine-mapping using JAM. If single-trait fine-mapping results are available, then it is not necessary to have Java JDK installed.
remotes::install_github("jennasimit/flashfm")
library(flashfm)
library(R2BGLiMS) # if running internal JAM functions for single-trait fine-mapping