findLinks: Find nearby pairs of clusters and calculate pairwise...

In MalteThodberg/CAGEfightR: Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor

Description

Finds all links or pairs of clusters within a certain distance of each other and then calculates the correlation between them. The links found can be restricted to only be between two classes, for example TSSs to enhancers.

Usage

findLinks(object, ...)

## S4 method for signature 'GRanges'
findLinks(object, maxDist = 10000L, directional = NULL)

## S4 method for signature 'RangedSummarizedExperiment'
findLinks(
  object,
  inputAssay,
  maxDist = 10000L,
  directional = NULL,
  corFun = stats::cor.test,
  vals = c("estimate", "p.value"),
  ...
)

Arguments

object	GRanges or RangedSummarizedExperiment: Clusters, possibly with expression for calculating correlations.
...	additional arguments passed to methods or ultimately corFun.
maxDist	integer: Maximum distance between links.
directional	character: Name of a column in object holding a grouping of the clusters. This must be a factor with two levels. The first level is used as the basis for calculating orientation (see below).
inputAssay	character: Name of assay holding expression values (if object is a RangedSummarizedExperiment)
corFun	function: Function for calculating pairwise correlations. See notes for supplying custom functions.
vals	character: Statistics extracted from the results produced by corFun. See notes for supplying custom functions.

Details

A custom function for calculation correlations can be supplied by the user. The output of this function must be a named list or vector of numeric values. The names of the vals to be extracted should be supplied to vals.

Value

A GInteractions holding the links, along with the distance between them and correlation estimate and p-value calculated from their expression. If a directional analysis was performed, the two anchors are always connecting members of the two classes and the orientation of the second anchor relative to the first is additionaly calculated (e.g. whether an enhancers is upstream or downstream of the TSS).

See Also

Other Spatial functions: findStretches(), trackLinks()

Examples

library(InteractionSet)

# Subset to highly expressed unidirectional clusters
TCs <- subset(exampleUnidirectional, score > 10)

# Find links within a certain distance
findLinks(TCs, inputAssay="counts", maxDist=10000L)

# To find TSS-to-enhancer type links, first merge the clusters:
colData(exampleBidirectional) <- colData(TCs)
rowRanges(TCs)$clusterType <- "TSS"
rowRanges(exampleBidirectional)$clusterType <- "Enhancer"
SE <- combineClusters(TCs, exampleBidirectional, removeIfOverlapping="object1")
rowRanges(SE)$clusterType <- factor(rowRanges(SE)$clusterType, levels=c("TSS", "Enhancer"))

# Calculate kendall correlations of TPM values:
SE <- calcTPM(SE, totalTags="totalTags")
findLinks(SE, inputAssay="TPM", maxDist=10000L, directional="clusterType", method="kendall")

MalteThodberg/CAGEfightR documentation built on Sept. 11, 2021, 4:42 a.m.