findConservedCDIMarkers: Find CDI-derived markers that are conserved across samples

In NMikolajewicz/scMiko: scRNAseq analysis functions. Developed using Seurat framework.

Find CDI-derived markers that are conserved across samples

Description

Find CDI-derived markers that are conserved across samples. For each sample (i.e., specified using group.by argument), FindCDIMarkers() is run, and the outputs from each sample are pooled. CDI scores are aggregated as means, whereas p values are pooled using the Fisher Method.

Usage

findConservedCDIMarkers(
  object,
  features.x,
  features.y = rownames(object),
  group.by,
  n.workers = 1,
  verbose = T,
  ...
)

Arguments

object	Seurat object
features.x	feature or meta feature. CDI between features.x and features.y are computed.
features.y	feature or meta feature. CDI between features.x and features.y are computed.
group.by	meta feature used to group data into independent samples.
n.workers	number of workers for parallel implementation. Default is 1 (no parallel).
verbose	print progress. Default is T.
...	additional arguments passed to findCDIMarkers(...)

Value

data.frame with pooled CDI scores.

Author(s)

Nicholas Mikolajewicz

See Also

findCDIMarkers

Examples

cdi.conserved <- FindConservedCDIMarkers(object = so.ps, features.x = "celltype", group.by = "sample", n.workers = 15)

NMikolajewicz/scMiko documentation built on June 28, 2023, 1:41 p.m.