analyzeQuantification {MPRAnalyze} | R Documentation |
epirical: the model is fitted as specified, enabling future empirical testing (either empirical p-value if negative controls are provided, or a global devience analysis, see details in 'test.empirical')
lrt: only available if negative controls are provided. A likelihood ratio test is used, with the null hypothesis a joint model of the controls and a given candidate sequence, and the alternative model being a separate model for controls and candidates.
analyzeQuantification(obj, dnaDesign = ~1, rnaDesign = ~1, BPPARAM = NULL)
obj |
the MpraObject |
dnaDesign |
the design of the DNA counts |
rnaDesign |
the design of the RNA counts |
BPPARAM |
a parallelization object created by BiocParallel. This overwrites the BPPARAM object set in the object creation. |
the MpraObject, with populated models
data <- simulateMPRA(tr = rep(2,10), nbatch=2, nbc=15) obj <- MpraObject(dnaCounts = data$obs.dna, rnaCounts = data$obs.rna, colAnnot = data$annot) obj <- estimateDepthFactors(obj, lib.factor = "batch", which.lib = "both") obj <- analyzeQuantification(obj, dnaDesign = ~ batch + barcode, rnaDesign = ~1)