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# fgsea
An R-package for fast preranked gene set enrichment analysis (GSEA). The package
implements a special algorithm to calculate the empirical enrichment score null distributions simulthaneously
for all the gene set sizes, which allows up to **several hundred times faster** execution time compared to original
Broad implementation. See [the preprint](http://biorxiv.org/content/early/2016/06/20/060012) for algorithmic details.
Full vignette can be found here: http://bioconductor.org/packages/devel/bioc/vignettes/fgsea/inst/doc/fgsea-tutorial.html
## Installation
```{r}
library(devtools)
install_github("ctlab/fgsea")
```
## Quick run
Loading libraries
```{r}
library(data.table)
library(fgsea)
library(ggplot2)
```
Loading example pathways and gene-level statistics:
```{r}
data(examplePathways)
data(exampleRanks)
```
Running fgsea (should take about 10 seconds):
```{r}
fgseaRes <- fgsea(pathways = examplePathways,
stats = exampleRanks,
minSize=15,
maxSize=500,
nperm=10000)
```
The head of resulting table sorted by p-value:
```
pathway pval padj ES NES nMoreExtreme size
1: 5990980_Cell_Cycle 0.0001221001 0.002356366 0.5388497 2.682641 0 369
2: 5990979_Cell_Cycle,_Mitotic 0.0001252976 0.002356366 0.5594755 2.738270 0 317
3: 5991210_Signaling_by_Rho_GTPases 0.0001310444 0.002356366 0.4238512 2.009963 0 231
4: 5991454_M_Phase 0.0001372872 0.002356366 0.5576247 2.548794 0 173
5: 5991023_Metabolism_of_carbohydrates 0.0001378930 0.002356366 0.4944766 2.240678 0 160
6: 5991209_RHO_GTPase_Effectors 0.0001386001 0.002356366 0.5248796 2.369573 0 157
7: 5991502_Mitotic_Metaphase_and_Anaphase 0.0001450326 0.002356366 0.6052907 2.633267 0 123
8: 5991600_Mitotic_Anaphase 0.0001452222 0.002356366 0.6015521 2.613626 0 122
9: 5991599_Separation_of_Sister_Chromatids 0.0001460707 0.002356366 0.6164600 2.661433 0 116
10: 5991130_Programmed_Cell_Death 0.0001465201 0.002356366 0.4537506 1.941445 0 108
```
One can make an enrichment plot for a pathway:
```{r}
plotEnrichment(examplePathways[["5991130_Programmed_Cell_Death"]],
exampleRanks) + labs(title="Programmed Cell Death")
```
Or make a table plot for a bunch of selected pathways:
```{r}
topPathwaysUp <- fgseaRes[ES > 0, ][head(order(pval), n=10), pathway]
topPathwaysDown <- fgseaRes[ES < 0, ][head(order(pval), n=10), pathway]
topPathways <- c(topPathwaysUp, rev(topPathwaysDown))
plotGseaTable(examplePathways[topPathways], exampleRanks, fgseaRes,
gseaParam = 0.5)
```
<img src="https://www.dropbox.com/s/uthtzn8wgo176f6/enrichmentTable.png?raw=1" width="600">
