locfitByCluster | R Documentation |
Local regression smoothing with a gaussian kernal, is applied independently to each cluster of genomic locations. Locations within the same cluster are close together to warrant smoothing across neighbouring locations.
locfitByCluster(y, x = NULL, cluster, weights = NULL, minNum = 7,
bpSpan = 1000, minInSpan = 0, verbose = TRUE)
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 locfit smoother |
minNum |
Clusters with fewer than |
bpSpan |
The span used when locfit smoothing. (Expressed in base pairs.) |
minInSpan |
Only smooth the region if there are at least this many locations in the span. |
verbose |
Boolean. Should progress be reported? |
This function is typically called by smoother
, which is in
turn called by bumphunter
.
fitted |
The smoothed data values |
smoothed |
A boolean vector indicating whether a given position was smoothed |
smoother |
always set to ‘locfit’. |
Rafael A. Irizarry and Kasper D. Hansen
smoother
, runmedByCluster
, loessByCluster
dat <- dummyData()
smoothed <- locfitByCluster(y=dat$mat[,1], cluster=dat$cluster, bpSpan = 1000,
minNum=7, minInSpan=5)
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