knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.