RunGscreend: run gscreend

In imkeller/gscreend: Analysis of pooled genetic screens

run gscreend

Description

run gscreend

Usage

RunGscreend(object, quant1 = 0.1, quant2 = 0.9, alphacutoff = 0.05)

Arguments

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)

Value

object

Examples

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)

imkeller/gscreend documentation built on March 14, 2024, 9:09 a.m.