NewPeakSeurat: Create a new peak-level Seurat object from the peak counts

In VCCRI/Sierra: PolyA counting and differential transcript usage analysis for scRNA-seq data

Create a new peak-level Seurat object from the peak counts

Description

Creates a new peak-level Seurat object from the peak counts and annotation table

Usage

NewPeakSeurat(
  peak.data,
  annot.info,
  project.name = "PolyA",
  cell.idents = NULL,
  tsne.coords = NULL,
  umap.coords = NULL,
  min.cells = 10,
  min.peaks = 200,
  norm.scale.factor = 10000,
  filter.gene.mismatch = TRUE,
  verbose = TRUE
)

Arguments

peak.data	matrix of peak counts
annot.info	peak annotation information
project.name	project name passed to the Seurat object creation
cell.idents	a list of cell identities (optional)
tsne.coords	a data-frame of t-SNE coordinates (optional)
umap.coords	a data-frame of UMAP coordinates (optional)
min.cells	minimum number of cells for retaining a peak
min.peaks	minimum number of peaks for retaining a cell
norm.scale.factor	scale factor for Seurat NormalizeData function
filter.gene.mismatch	whether to filter out peaks with ambiguous gene mappings
verbose	whether to print output

Value

a new peak-level Seurat object

Examples

                             
## Load example data for two peaks from the Cxcl12 gene
extdata_path <- system.file("extdata",package = "Sierra")
load(paste0(extdata_path, "/Cxcl12_example.RData"))
load(paste0(extdata_path, "/TIP_cell_info.RData"))

## Create an Seurat object holding the peak data
peaks.seurat <- NewPeakSeurat(peak.data = peak.counts, 
                        annot.info = peak.annotations, 
                        cell.idents = tip.populations, 
                        tsne.coords = tip.tsne.coordinates,
                        min.cells = 0, min.peaks = 0)
                             

VCCRI/Sierra documentation built on July 3, 2023, 6:39 a.m.