smoother | R Documentation |
Apply smoothing to values typically representing the difference between two populations across genomic regions.
smoother(y, x = NULL, cluster, weights = NULL, smoothFunction,
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 smoother. |
smoothFunction |
A function to be used for smoothing the estimate
of the genomic profile. Two functions are provided by the package:
|
verbose |
Boolean. Should progress be reported? |
... |
Further arguments to be passed to |
This function is typically called by bumphunter prior to identifying
candidate bump regions. Smoothing is carried out within regions defined
by the cluster
argument.
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 |
The name of the smoother used |
Rafael A. Irizarry and Martin J. Aryee
loessByCluster
, runmedByCluster
dat <- dummyData()
# Enable parallelization
require(doParallel)
registerDoParallel(cores = 2)
## loessByCluster
smoothed <- smoother(y=dat$mat[,1], cluster=dat$cluster, smoothFunction=loessByCluster,
bpSpan = 1000, minNum=7, minInSpan=5, maxSpan=1)
## runmedByCluster
smoothed <- smoother(y=dat$mat[,1], cluster=dat$cluster, smoothFunction=runmedByCluster,
k=5, endrule="constant")
# cleanup, for Windows
bumphunter:::foreachCleanup()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.