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.
FindMarkersNode(object, node, tree.use = NULL, genes.use = NULL,
logfc.threshold = 0.25, test.use = "wilcox", assay.type = "RNA", ...)Seurat object
The node in the phylogenetic tree to use as a branch point
Can optionally pass the tree to be used. Default uses the tree in object@cluster.tree
Genes to test. Default is to use all genes
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 logfc.threshold speeds up the function, but can miss weaker signals.
Denotes which test to use. Available options are:
"wilcox" : Wilcoxon rank sum test (default)
"bimod" : Likelihood-ratio test for single cell gene expression, (McDavid et al., Bioinformatics, 2013)
"roc" : Standard AUC classifier
"t" : Student's t-test
"tobit" : Tobit-test for differential gene expression (Trapnell et al., Nature Biotech, 2014)
"poisson" : Likelihood ratio test assuming an underlying poisson distribution. Use only for UMI-based datasets
"negbinom" : Likelihood ratio test assuming an underlying negative binomial distribution. Use only for UMI-based datasets
"MAST : GLM-framework that treates cellular detection rate as a covariate (Finak et al, Genome Biology, 2015)
"DESeq2 : DE based on a model using the negative binomial distribution (Love et al, Genome Biology, 2014)
Type of assay to fetch data for (default is RNA)
Additional arguments passed to FindMarkers
Matrix containing a ranked list of putative markers, and associated statistics (p-values, ROC score, etc.)
# NOT RUN {
FindMarkersNode(pbmc_small, 5)
# }
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