| NewPeakSCE | R Documentation | 
Creates a new peak-counts single-cell experiment object from the peak counts and annotation table
NewPeakSCE(
  peak.data,
  annot.info,
  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
)
peak.data | 
 matrix of peak counts  | 
annot.info | 
 peak annotation information  | 
cell.idents | 
 named list of cell identities to be used for DU analysis  | 
tsne.coords | 
 data-frame of t-SNE coordinates. Rownames should correspond to cell names.  | 
umap.coords | 
 data-frame of UMAP coordinates. Rownames should correspond to cell names.  | 
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 log normalisation function  | 
filter.gene.mismatch | 
 whether to filter out peaks with ambiguous gene mappings  | 
verbose | 
 whether to print output  | 
a new peak-level SCE object
 ## 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 SCE object holding the peak data
peaks.sce <- NewPeakSCE(peak.data = peak.counts, 
                        annot.info = peak.annotations, 
                        cell.idents = tip.populations, 
                        tsne.coords = tip.tsne.coordinates,
                        min.cells = 0, min.peaks = 0)
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