hm {perturbatr} | R Documentation |
Analyse multiple different genetic perturbation screens at once using a hierarchical model. The model estimates general relative effect sizes for genes across all experiments. This could for instance be a pan-pathogenic host factor, i.e. a gene that decisively impacts the life-cycle of multiple pathogens.
hm(obj, formula = Readout ~ Condition + (1 | GeneSymbol) + (1 | Condition:GeneSymbol), drop = TRUE, weights = 1, bootstrap.cnt = 0) ## S4 method for signature 'PerturbationData' hm(obj, formula = Readout ~ Condition + (1 | GeneSymbol) + (1 | Condition:GeneSymbol), drop = TRUE, weights = 1, bootstrap.cnt = 0)
obj |
an |
formula |
a |
drop |
boolean if genes that are not found in every Condition should be dropped |
weights |
a numeric vector used as weights for the single perturbations |
bootstrap.cnt |
the number of bootstrap runs you want to do in order to estimate a significance level for the gene effects |
returns a HMAnalysedPerturbationData
object
data(rnaiscreen) res <- hm(rnaiscreen)