runDiffExpression: runDiffExpression

In IMB-Computational-Genomics-Lab/ascend: ascend - Analysis of Single Cell Expression, Normalisation, and Differential expression

Description

This function uses a combined Likelihood-Ratio Test (LRT) for discrete/continuous models to examine differentially expressed genes, on a gene-gene level. This method was adapted from the method published by [McDavid et al. 2013](https://doi.org/10.1093/bioinformatics/bts714).

Usage

runDiffExpression(object, group = NULL, condition.a = NULL,
  condition.b = NULL, subsampling = FALSE, ngenes = NULL)

Arguments

object	An EMSet that has undergone filtering and normalisation
group	A column in colInfo that contains a vector of conditions
condition.a	Condition(s) of first group of cells
condition.b	Condition(s) of second group of cells
subsampling	TRUE or FALSE (Default). Whether or not to subsample from larger group of cells if cell populations are uneven
ngenes	Test this number of the most variable genes in the dataset

Value

A data frame with DE analysis results

Examples

# Load example EMSet
em_set <- ascend::analyzed_set

# Compare cluster 1 vs cluster 2
cluster1_vs_cluster2 <- runDiffExpression(em_set, group = "cluster",
condition.a = 1, condition.b = 2, subsampling = FALSE, ngenes = 1500)

IMB-Computational-Genomics-Lab/ascend documentation built on Aug. 29, 2019, 4:10 a.m.