computeFC-methods: Compute fold changes and find gene signatures.

In edroaldo/fusca: Framework for Unified Single-Cell Analysis

Compute fold changes and find gene signatures.

Description

Compute fold changes and find gene signatures in each group of cells.

Usage

computeFC(
  object,
  assay.type = "RNA",
  column = "population",
  pos.only = TRUE,
  min.pct = 0.1,
  fc.threshold = 0.25
)

## S4 method for signature 'CellRouter'
computeFC(
  object,
  assay.type = "RNA",
  column = "population",
  pos.only = TRUE,
  min.pct = 0.1,
  fc.threshold = 0.25
)

Arguments

object	CellRouter object
assay.type	character; the type of data to use.
column	character; column in the metadata table to group cells for differential expression. For example, if 'population' is specified, population-specific gene signatures will be identified.
pos.only	logical; only uses genes upregulated.
min.pct	numeric; minimum percentage.
fc.threshold	numerical; fold change threshold.

Value

CellRouter object with the signatures slot updated. This slot contains a list with a dataframe for each group containing information about mean.np, mean.p, fc (fold changes), pv (p-value), p.adj (p-value adjusted.).

edroaldo/fusca documentation built on March 1, 2023, 1:43 p.m.