Lightweight Iterative Gene set Enrichment in R (LIGER)

Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states. The original algorithm is detailed in Subramanian, Tamayo, et al. with Java implementations available through the Broad Institute.

The liger package provides a lightweight R implementation of this enrichment test on a list of values. Given a list of values, such as p-values or log-fold changes derived from differential expression analysis or other analyses comparing biological states, this package enables you to test a priori defined set of genes for enrichment to enable interpretability of highly significant or high fold-change genes.

Tutorials

• Gene Set Enrichment Analysis with LIGER
• Highlighting the power of gene set enrichment analysis using simulation
• Interpreting Enrichment Scores and Edge Values

Sample plots

Testing individual gene sets

> gsea(values=vals, geneset=gs, mc.cores=1, plot=TRUE)

Testing multiple gene sets

> ptm <- proc.time()
> bulk.gsea(vals, org.Hs.GO2Symbol.list[1:10])
                  p.val     q.val     sscore       edge
  GO:0000002 0.00009999 0.0000000  2.6139724  70.912194
  GO:0000003 0.25647435 0.4074000  0.5400972  13.170093
  GO:0000012 0.24347565 0.4074000  0.5550191   8.392397
  GO:0000014 0.13428657 0.3779000  0.6906745  -4.458762
  GO:0000018 0.14448555 0.7215200 -0.6498716  11.111976
  GO:0000022 0.33446655 0.8023667 -0.5014560 -11.015244
> proc.time() - ptm
   user  system elapsed
  6.200   0.065   6.414

> ptm <- proc.time()
> iterative.bulk.gsea(values=vals, set.list=org.Hs.GO2Symbol.list[1:10])
                  p.val   q.val     sscore       edge
  GO:0000002 0.00009999 0.00000  2.6054741  70.912194
  GO:0000003 0.25867413 0.41730  0.5352656  13.170093
  GO:0000012 0.24727527 0.41730  0.5545500   8.392397
  GO:0000014 0.14128587 0.40300  0.6903051  -4.458762
  GO:0000018 0.13988601 0.72684 -0.6485933  11.111976
  GO:0000022 0.31666833 0.81440 -0.4975180 -11.015244
> proc.time() - ptm
    user  system elapsed
  11.250   0.107   5.320

Install

# The easiest way to get liger is to install it from CRAN:
install.packages("liger")

# Or get the latest development version from GitHub:
require(devtools)
devtools::install_github("JEFworks/liger")

Contributing

We welcome any bug reports, enhancement requests, and other contributions. To submit a bug report or enhancement request, please use the liger GitHub issues tracker. For more substantial contributions, please fork this repo, push your changes to your fork, and submit a pull request with a good commit message.