DE_analyze: Differential Expression Analysis

In compbiomed/BatchQC: Batch Effects Quality Control Software

Differential Expression Analysis

Description

This function runs DE analysis on a count matrix (DESeq) or a normalized log or log-CPM matrix (limma) contained in the se object

Usage

DE_analyze(se, method, batch, conditions, assay_to_analyze)

Arguments

se	SummarizedExperiment object
method	DE analysis method option (either 'DESeq2' or 'limma')
batch	metadata column in the se object representing batch
conditions	metadata columns in the se object representing additional analysis covariates
assay_to_analyze	Assay in the se object (either counts for DESeq2 or normalized data for limma) for DE analysis

Value

A named list containing the log2FoldChange, pvalue and adjusted pvalue (padj) for each analysis returned by DESeq2 or limma

Examples

library(scran)
se <- mockSCE()
differential_expression <- BatchQC::DE_analyze(se = se,
                                                method = "DESeq2",
                                                batch = "Treatment",
                                                conditions = c(
                                                "Mutation_Status"),
                                                assay_to_analyze = "counts")
pval_summary(differential_expression)
pval_plotter(differential_expression)

compbiomed/BatchQC documentation built on Nov. 6, 2024, 12:17 a.m.