FindMarkersNode: Gene expression markers of identity classes defined by a...

In nukappa/seurat_v2: Seurat : R toolkit for single cell genomics

Description

Finds markers (differentially expressed genes) based on a branching point (node) in the phylogenetic tree. Markers that define clusters in the left branch are positive markers. Markers that define the right branch are negative markers.

Usage

FindMarkersNode(object, node, tree.use = NULL, genes.use = NULL,
  thresh.use = log(2), test.use = "bimod", ...)

Arguments

object	Seurat object
node	The node in the phylogenetic tree to use as a branch point
tree.use	Can optionally pass the tree to be used. Default uses the tree in [e-mail]
genes.use	Genes to test. Default is to use all genes
thresh.use	Limit testing to genes which show, on average, at least X-fold difference (log-scale) between the two groups of cells. Default is 0.25 Increasing thresh.use speeds up the function, but can miss weaker signals.
test.use	Denotes which test to use. Seurat currently implements "bimod" (likelihood-ratio test for single cell gene expression, McDavid et al., Bioinformatics, 2011, default), "roc" (standard AUC classifier), "t" (Students t-test), and "tobit" (Tobit-test for differential gene expression, as in Trapnell et al., Nature Biotech, 2014), 'poisson', and 'negbinom'. The latter two options should only be used on UMI datasets, and assume an underlying poisson or negative-binomial distribution
...	Additional arguments passed to FindMarkers

Value

Matrix containing a ranked list of putative markers, and associated statistics (p-values, ROC score, etc.)

nukappa/seurat_v2 documentation built on May 24, 2019, 9:57 a.m.