analyzeQuantification: Perform quantitative analysis on the MPRA data. This analysis...

In YosefLab/MPRAnalyze: Statistical Analysis of MPRA data

Description

• 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.

Usage

analyzeQuantification(obj, dnaDesign = ~1, rnaDesign = ~1, BPPARAM = NULL)

Arguments

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.

Value

the MpraObject, with populated models

Examples

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)

YosefLab/MPRAnalyze documentation built on Nov. 14, 2020, 2:35 a.m.