runLimma {debrowser} | R Documentation |
Run Limma algorithm on the selected conditions. Output is to be used for the interactive display.
runLimma(data = NULL, columns = NULL, conds = NULL, normfact = c("none", "TMM", "RLE", "upperquartile"), fitType = c("ls", "robust"), normBet = c("none", "scale", "quantile", "cyclicloess", "Aquantile", "Gquantile", "Rquantile", "Tquantile"), rowsum.filter = 10)
data, |
A matrix that includes all the expression raw counts, rownames has to be the gene, isoform or region names/IDs |
columns, |
is a vector that includes the columns that are going to be analyzed. These columns has to match with the given data. |
conds, |
experimental conditions. The order has to match with the column order |
normfact, |
Calculate normalization factors to scale the raw library sizes. Values can be "TMM","RLE","upperquartile","none". |
fitType, |
fitting method; "ls" for least squares or "robust" for robust regression |
normBet, |
Normalizes expression intensities so that the intensities or log-ratios have similar distributions across a set of arrays. |
rowsum.filter, |
regions/genes/isoforms with total count (across all samples) below this value will be filtered out |
Limma results
x <- runLimma()