Seurat (version 2.3.4)

FindAllMarkersNode: Find all markers for a node

Description

This function finds markers for all splits at or below the specified node

Usage

FindAllMarkersNode(object, node = NULL, genes.use = NULL,
  logfc.threshold = 0.25, test.use = "wilcox", min.pct = 0.1,
  min.diff.pct = 0.05, print.bar = TRUE, only.pos = FALSE,
  max.cells.per.ident = Inf, return.thresh = 0.01, do.print = FALSE,
  random.seed = 1, min.cells.gene = 3, min.cells.group = 3,
  assay.type = "RNA", ...)

Arguments

object

Seurat object. Must have [e-mail] slot filled. Use BuildClusterTree() if not.

node

Node from which to start identifying split markers, default is top node.

genes.use

Genes to test. Default is 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.

test.use

Denotes which test to use. Seurat currently implements "bimod" (likelihood-ratio test for single cell gene expression, McDavid et al., Bioinformatics, 2013, 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.

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 expression

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

print.bar

Print a progress bar once expression testing begins (uses pbapply to do this)

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.

return.thresh

Only return markers that have a p-value < return.thresh, or a power > return.thresh (if the test is ROC)

do.print

Print status updates

random.seed

Random seed for downsampling

min.cells.gene

Minimum number of cells expressing the gene in at least one of the two groups, currently only used for poisson and negative binomial tests

min.cells.group

Minimum number of cells in one of the groups

assay.type

Type of assay to fetch data for (default is RNA)

…

Additional parameters to pass to specific DE functions

Value

Returns a dataframe with a ranked list of putative markers for each node and associated statistics

Examples

# NOT RUN {
pbmc_small

FindAllMarkersNode(pbmc_small)

# }