identifyDifferentialGenes_in_multiple_clusters_vs_the_rest_of_clusters: Identify differentially expressed genes between multiple...

In supatt-lab/SingCellaR: SingCellaR: an integrative analysis tool for single-cell RNA sequencing (scRNA-seq) data

Identify differentially expressed genes between multiple selected clusters vs the rest of clusters

Description

Identify differentially expressed genes between multiple selected clusters vs the rest of clusters

Usage

identifyDifferentialGenes_in_multiple_clusters_vs_the_rest_of_clusters(
  object,
  cluster.ids = c(),
  method = c("wilcoxon"),
  cluster.type = c("louvain", "kmeans", "merged_walktrap", "merged_louvain",
    "merged_kmeans"),
  min.log2FC = 0.25,
  min.expFraction = 0.3,
  write.to.file = ""
)

Arguments

object	The SingCellaR object.
method	The differential gene expression testing method. Default 'wilcoxon' test
cluster.type	The type of clustering method.
min.log2FC	The minimum log2FC cutoff. Default 0.25
min.expFraction	The minimum fraction of expressing cell frequency cutoff. Default 0.3
write.to.file	The output file name.
cluster_id	The specified cluster ID (e.g. cluster1)

Value

a dataframe of differentially expressed genes.

supatt-lab/SingCellaR documentation built on Aug. 24, 2023, 5:49 p.m.