ComputePairWiseDE: Find markers (differentially expressed genes) between two...
In linquynus/RCAv2-beta: Reference Component Analysis

Find markers (differentially expressed genes) between two group of cells.

ComputePairWiseDE(
  object,
  cells.1 = NULL,
  cells.2 = NULL,
  features = NULL,
  logfc.threshold = 1.5,
  test.use = "wilcox",
  min.pct = 0.25,
  min.diff.pct = -Inf,
  verbose = TRUE,
  only.pos = FALSE,
  max.cells.per.ident = Inf,
  random.seed = 1,
  min.cells.group = 3,
  pseudocount.use = 1,
  MeanExprsThrs = 0,
  p.adjust.methods = "BH"
)

`object`	dataMatrix of genes (rows) x cells (columns) expression matrix (log normalized value)
`cells.1`	Vector of cell names belonging to group 1
`cells.2`	Vector of cell names belonging to group 2
`features`	Genes to test. Default is NULL which mean to use all genes
`logfc.threshold`	Limit testing to genes which show, on average, at least X-fold difference (log-scale) between the two groups of cells. Default is log(1.5)
`test.use`	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.
`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
`verbose`	Print a progress bar once expression testing begins
`only.pos`	Only return positive markers (FALSE by default)
`max.cells.per.ident`	Down sample each identity class to a max number. Default is no downsampling. Not activated by default (set to Inf)
`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.
`MeanExprsThrs`	a minimum expression threshold of average cluster expression for a gene to be considered a DE gene. the mean expression value is in the linear scale!
`p.adjust.methods`	correction method for calculating qvalue. default is BH (or FDR)

returnObj returnObj = list( 'list CompGeneList: List of genes for which the DE statistical test was performed for each pairwise cluster comparison list qValueList: list of q-values from the DE statistical test for genes where test was performed for each pairwise cluster comparison list log2FCList: list of log2-fold-changes from the DE statistical test for genes where test was performed for each pairwise cluster comparison= character vector deGeneUnion: union of top ndeg DE genes from up- and down- regulated set for all pairwise comparison numeric matrix deCountMatrix: matrix with number of DE genes for each pairwise cluster comparison list deGeneRegulationList: list of up and down regulated DE genes for each pairwise cluster comparison ordered by log2-fold-change list log2FCDEList: list of log2-fold-change for up and down regulated DE genes for each pairwise cluster comparison - corresponds to same order as in deGeneRegulationList list qValueDEList: list of q-values for up and down regulated DE genes for each pairwise cluster comparison - corresponds to same order as in deGeneRegulationList list upregulatedDEGeneList: list of cluster-specific upregulated DE genes list downregulatedDEGeneList: list of cluster-specific downregulated DE genes )

linquynus/RCAv2-beta documentation built on Aug. 9, 2020, 12:34 a.m.