giaever: Yeast Gene-Knockout Fitness Data

In GraphAT: Graph Theoretic Association Tests

Description

This data set contains fitness deficiency scores from gene knockout experiments involving yeast grown under a variety of altered environments (e.g. acid, heat, sorbitol, etc.)

Usage

data(giaever)

Format

A matrix whose rows are the 5922 genes knocked out and whose columns are the 32 experimental conditions.

Source

http://gobi.lbl.gov/YeastFitnessData

References

Giaever, G. et al. 2002 “Functional profiling of the Saccharomyces cerevisiae genome.” Nature 418, 387–391.

Examples

data(giaever)

## Find the 3000 most variable genes, according to sd/mean:
varMeas <- function(vec, na.rm=TRUE) 
{
    if(na.rm)
      vec <- vec[!is.na(vec)]
    if(length(vec) == 0)
      measure <- NA
    else
      measure <- sd(vec)/mean(vec)
    return(measure)
}

variability <- apply(giaever, 1, varMeas)

rks <- rank(variability)

giaever3000 <- giaever[rks>length(rownames(giaever))-3000,]

GraphAT documentation built on Nov. 8, 2020, 5:01 p.m.