prepSCE: Prepare SCE for DS analysis

In muscat: Multi-sample multi-group scRNA-seq data analysis tools

Description

...

Usage

prepSCE(
  x,
  kid = "cluster_id",
  sid = "sample_id",
  gid = "group_id",
  drop = FALSE
)

Arguments

x	a SingleCellExperiment.
kid, sid, gid	character strings specifying the colData(x) columns containing cluster assignments, unique sample identifiers, and group IDs (e.g., treatment).
drop	logical. Specifies whether colData(x) columns besides those specified as cluster_id,sample_id,group_id should be retained (default drop = FALSE) or removed (drop = TRUE).

Value

a SingleCellExperiment.

Author(s)

Helena L Crowell

Examples

# generate random counts
ng <- 50
nc <- 200
counts <- matrix(sample(ng * nc), nrow = ng, ncol = nc)
    
# generate some cell metadata
gids <- sample(c("groupA", "groupB"), nc, TRUE)   
sids <- sample(paste0("sample", seq_len(3)), nc, TRUE) 
kids <- sample(paste0("cluster", seq_len(5)), nc, TRUE) 
batch <- sample(seq_len(3), nc, TRUE)

# construct SCE
library(SingleCellExperiment)
sce <- SingleCellExperiment(
  assays = list(counts = counts),
  colData = data.frame(group = gids, id = sids, cluster = kids, batch))
    
# prep. for workflow
sce <- prepSCE(sce, kid = "cluster", sid = "id", gid = "group")
head(colData(sce))
metadata(sce)$experiment_info

muscat documentation built on Nov. 8, 2020, 7:47 p.m.