bumphunter (version 1.12.0)

runmedByCluster: Apply running median smoothing to values within each spatially-defined cluster

Description

Running median smoothing is applied independently to each cluster of genomic locations. Locations within the same cluster are close together to warrant smoothing across neighbouring locations.

Usage

runmedByCluster(y, x = NULL, cluster, weights = NULL, k = 5, endrule = "constant", verbose = TRUE)

Arguments

y

A vector or matrix of values to be smoothed. If a matrix, each column represents a sample.

x

The genomic location of the values in y.

cluster

A vector indicating clusters of locations. A cluster is typically defined as a region that is small enough that it makes sense to smooth across neighbouring locations. Smoothing will only be applied within a cluster, not across locations from different clusters.

weights

weights used by the smoother.

k

integer width of median window; must be odd. See runmed

endrule

character string indicating how the values at the beginning and the end (of the data) should be treated. See runmed.

verbose

Boolean. Should progress be reported?

Value

fitted

The smoothed data values

smoothed

A boolean vector indicating whether a given position was smoothed

spans

The span used by the loess smoother. One per cluster.

clusterL

The number of locations in each cluster.

smoother

always set to ‘runmed’.

Details

This function is typically called by smoother, which is in turn called by bumphunter.

See Also

smoother, loessByCluster. Also see runmed.

Examples

dat <- dummyData()
smoothed <- runmedByCluster(y=dat$mat[,1], cluster=dat$cluster,
                            k=5, endrule="constant")