rliger (version 2.0.1)

linkGenesAndPeaks: Linking genes to putative regulatory elements

Description

Evaluate the relationships between pairs of genes and peaks based on specified distance metric. Usually used for inferring the correlation between gene expression and imputed peak counts for datasets without the modality originally (i.e. applied to imputeKNN result).

Usage

linkGenesAndPeaks(
  object,
  useDataset,
  pathToCoords,
  useGenes = NULL,
  method = c("spearman", "pearson", "kendall"),
  alpha = 0.05,
  verbose = getOption("ligerVerbose", TRUE),
  path_to_coords = pathToCoords,
  genes.list = useGenes,
  dist = method
)

Value

A sparse matrix with peak names as rows and gene names as columns, with each element indicating the correlation between peak i and gene j, 0 if the gene and peak are not significantly linked.

Arguments

object

A liger object, with datasets that is of ligerATACDataset class in the datasets slot.

useDataset

Name of one dataset, with both normalized gene expression and normalized peak counts available.

pathToCoords

Path tothe gene coordinates file, usually a BED file.

useGenes

Character vector of gene names to be tested. Default NULL uses all genes available in useDataset.

method

Choose the type of correlation to calculate, from "spearman", "pearson" and "kendall". Default "spearman"

alpha

Numeric, significance threshold for correlation p-value. Peak-gene correlations with p-values below this threshold are considered significant. Default 0.05.

verbose

Logical. Whether to show information of the progress. Default getOption("ligerVerbose") or TRUE if users have not set.

path_to_coords, genes.list, dist

Deprecated. See Usage section for replacement.

See Also

imputeKNN

Examples

# \donttest{
if (requireNamespace("RcppPlanc", quietly = TRUE) &&
    requireNamespace("GenomicRanges", quietly = TRUE) &&
    requireNamespace("IRanges", quietly = TRUE) &&
    requireNamespace("psych", quietly = TRUE)) {
    bmmc <- normalize(bmmc)
    bmmc <- selectGenes(bmmc)
    bmmc <- scaleNotCenter(bmmc)
    bmmc <- runINMF(bmmc, miniBatchSize = 100)
    bmmc <- quantileNorm(bmmc)
    bmmc <- normalizePeak(bmmc)
    bmmc <- imputeKNN(bmmc, reference = "atac", queries = "rna")
    corr <- linkGenesAndPeaks(
        bmmc, useDataset = "rna",
        pathToCoords = system.file("extdata/hg19_genes.bed", package = "rliger")
    )
}
# }