dataDE: Compute pairwise DE genes for supervised clustering result.
In linquynus/RCAv2-beta: Reference Component Analysis

Compute pairwise DE genes for supervised clustering result.

dataDE(
  rca.obj,
  logFoldChange = 1.5,
  method = "wilcox",
  mean.Exp = 0.5,
  deepsplit = 1,
  min.pct = 0.25,
  min.diff.pct = -Inf,
  random.seed = 1,
  min.cells.group = 3,
  pseudocount.use = 1,
  p.adjust.methods = "BH",
  top.genes.per.cluster = 10,
  pairwise = FALSE
)

`rca.obj`	RCA object.
`logFoldChange`	Log fold change required to call gene DE.
`method`	Denotes which test to use. Available options are: "wilcox" : Identifies differentially expressed genes between two groups of cells using a Wilcoxon Rank Sum test (default) "bimod" : Likelihood-ratio test for single cell gene expression, (McDavid et al., Bioinformatics, 2013) "roc" : Identifies 'markers' of gene expression using ROC analysis. For each gene, evaluates (using AUC) a classifier built on that gene alone, to classify between two groups of cells. An AUC value of 1 means that expression values for this gene alone can perfectly classify the two groupings (i.e. Each of the cells in cells.1 exhibit a higher level than each of the cells in cells.2). An AUC value of 0 also means there is perfect classification, but in the other direction. A value of 0.5 implies that the gene has no predictive power to classify the two groups. Returns a 'predictive power' (abs(AUC-0.5) * 2) ranked matrix of putative differentially expressed genes. "t" : Identify differentially expressed genes between two groups of cells using the Student's t-test.
`mean.Exp`	Minimum mean expression of a gene to be considered in the DE gene calculation
`deepsplit`	If hclust was used for clustering, the desired deepsplit can be specified here.. Values can range from 0 to 4. Default is 1.
`min.pct`	only test genes that are detected in a minimum fraction of min.pct cells in either of the two populations. Meant to speed up the function by not testing genes that are very infrequently expressed. Default is 0.25
`min.diff.pct`	only test genes that show a minimum difference in the fraction of detection between the two groups. Set to -Inf by default
`random.seed`	Random seed for downsampling. default is 1
`min.cells.group`	Minimum number of cells in one of the groups
`pseudocount.use`	Pseudocount to add to averaged expression values when calculating logFC. 1 by default.
`p.adjust.methods`	correction method for calculating qvalue. default is BH (or FDR)
`top.genes.per.cluster`	Number of top DE genes to be considered per cluster
`pairwise`	Flag indicating whether DE genes should be compared derived in pairwise manner or 1 cluster vs all others (Default).