tingverse is a set of basic functions for Bioinformatics at the Ting Lab of the Massachusetts General Hospital Cancer Center. It was one of my projects when I was a summer intern in the Ting Lab. I worked on it during the summer of 2022 and the summer of 2023. It showcases what I learned over the course of those two summers, and it is no longer updated, nor is it representative of current best practices that I employ in my work.
Mike Raabe and Peter Richieri are the two people who mentored me during my summer internships. Much of the code in this repository was influenced by their previous work.
You can install and load the tingverse package by running the following lines in R:
install.packages('devtools')
library(devtools)
devtools::install_github('ccnawrocki/tingverse')
library(tingverse)
The tingverse has multiple dependencies. R makes updating dependencies very painful, so, for simplicity's sake, install and load each dependency as follows in order to use the tingverse.
install.packages("tidyverse")
install.packages("ggrepel")
install.packages("parallel")
library(tidyverse)
library(ggrepel)
library(parallel)
The GSEA functionality of the tingverse is a wrapper for clusterProfiler functions that depend on certain gene set databases available for download through Bioconductor. These two databases are about 80 MB each, which is not trivial. Thus, if you do not plan to use the GSEA functionality of the tingverse, then do not download these databases. Otherwise, you can download these databases as follows:
install.packages("BiocManager")
library(BiocManager)
BiocManager::install("clusterProfiler")
BiocManager::install("org.Hs.eg.db")
BiocManager::install("org.Mm.eg.db")
library(clusterProfiler)
library(org.Hs.eg.db)
library(org.Mm.eg.db
Once you have downloaded the clusterProfiler package and these databases, you will have access to the tingverse's full capabilities.