Post-GWAS enrichment, colocalization, TWAS and Mendelian Randomization to integrate molecular QTL and GWAS. • pecotmr

This R package, pecotmr implements post-GWAS enrichment, colocalization, TWAS and Mendelian Randomization to integrate QTL and GWAS analysis, mostly based on fine-mapped single effects model although a number of other approaches are included for handy availiability in daily research. pecotmr also stands for a probabilistic ecosystem consolidating a range of established and new models into a streamlined, user-friendly interface complete with well-documented examples that will help getting your analysis done by tomorrow if you start working on it today!

This project was developed by NIH/NIA FunGen-xQTL Project Working Group members with applications to FunGen-xQTL data analysis.

Quick Start

To install the latest version of the pecotmr package from GitHub, use BiocManager:

install.packages(c("BiocManager", "remotes"))
BiocManager::install("StatFunGen/pecotmr")

If you have cloned the repository locally, you can install the package with the install_local function from devtools. Assuming your working directory contains the pecotmr repository, run this code to install the package:

devtools::install_local("pecotmr",build_vignettes = TRUE)

devtools should automatically install all required packages if they are not installed already. If automatic installation fails for some packages and you are unable to fix them, please try to use our conda package instead.

To install using conda or micromamba for our released version,

micromamba install -c dnachun -c conda-forge -c bioconda r-pecotmr

To still use devtools to build pecotmr from source we suggest you use pixi to set up a local environment with all dependencies:

.github/workflows/create_toml_from_yaml.sh .
pixi install
pixi shell

Now you should be able to build pecotmr from source.

Developer’s notes

When any changes are made to roxygen2 markup or the C++ code in the src directory, run devtools::document() to update the RcppExports.cpp, the package namespaces (see NAMESPACE), and the package documentation files (in the “man” subdirectory),
These are the R commands to build the website (make sure you are connected to Internet while running these commands):
```
pkgdown::build_site_github_pages(new_process = FALSE, install = TRUE)
```
The website is automatically deployed to https://statfungen.github.io/pecotmr on push to main via GitHub Actions.

To format R codes in the R folder,

for i in `ls R/*.R`; do bash inst/misc/format_r_code.sh $i; done

After editing C++ code in the src directory, please use uncrustify (version >=0.74.0, available from conda-forge) to format the code using configuration file inst/misc/uncrustify_default.cfg. For example:

uncrustify -c inst/misc/uncrustify_default.cfg --replace --no-backup -l CPP src/qtl_enrichment.cpp
uncrustify -c inst/misc/uncrustify_default.cfg --replace --no-backup -l CPP src/qtl_enrichment.hpp

Prior to submitting the package to Bioconductor, the following modifications need to be made: (1) remove the Remotes: entry in DESCRIPTION; and

remove the fastenloc.Rmd vignette.