RunGscreend {gscreend} | R Documentation |
run gscreend
RunGscreend(object, quant1 = 0.1, quant2 = 0.9, alphacutoff = 0.05)
object |
PoolScreenExp object |
quant1 |
lower quantile for least quantile of squares regression (default: 0.1) |
quant2 |
upper quantile for least quantile of squares regression (default: 0.9) |
alphacutoff |
alpha cutoff for alpha-RRA (default: 0.05) |
object
raw_counts <- read.table( system.file('extdata', 'simulated_counts.txt', package = 'gscreend'), header=TRUE) # Create the PoolScreenExp to be analyzed counts_matrix <- cbind(raw_counts$library0, raw_counts$R0_0, raw_counts$R1_0) rowData <- data.frame(sgRNA_id = raw_counts$sgrna_id, gene = raw_counts$Gene) colData <- data.frame(samplename = c('library', 'R1', 'R2'), timepoint = c('T0', 'T1', 'T1')) library(SummarizedExperiment) se <- SummarizedExperiment(assays=list(counts=counts_matrix), rowData=rowData, colData=colData) pse <- createPoolScreenExp(se) # Run Analysis pse_an <- RunGscreend(pse)