findRegions | R Documentation |
Find genomic regions for which a numeric vector is above (or below) predefined thresholds. In other words, this function finds the candidate Differentially Expressed Regions (candidate DERs). This is similar to regionFinder and is a helper function for calculatePvalues.
findRegions(
position = NULL,
fstats,
chr,
oneTable = TRUE,
maxClusterGap = 300L,
cutoff = quantile(fstats, 0.99, na.rm = TRUE),
segmentIR = NULL,
smooth = FALSE,
weights = NULL,
smoothFunction = bumphunter::locfitByCluster,
...
)
position |
A logical Rle of genomic positions. This is generated in
loadCoverage. Note that it gets updated in preprocessCoverage
if |
fstats |
A numeric Rle with the F-statistics. Usually obtained using calculateStats. |
chr |
A single element character vector specifying the chromosome name. |
oneTable |
If |
maxClusterGap |
This determines the maximum gap between candidate DERs.
It should be greater than |
cutoff |
Threshold applied to the |
segmentIR |
An IRanges object with the genomic positions that are potentials DERs. This is used in calculatePvalues to speed up permutation calculations. |
smooth |
Whether to smooth the F-statistics ( |
weights |
Weights used by the smoother as described in smoother. |
smoothFunction |
A function to be used for smoothing the F-statistics.
Two functions are provided by the |
... |
Arguments passed to other methods and/or advanced arguments. Advanced arguments:
Passed to extendedMapSeqlevels and the internal function
When |
regionFinder adapted to Rle world.
Either a GRanges or a GRangesList as determined by oneTable
.
Each of them has the following metadata variables.
The mean of the values of y
for the given region.
The absolute value of the sum of the values of y
for
the given region.
The start position of the region in terms of the index
for y
.
The end position of the region in terms of the index for
y
.
The cluser ID.
The total length of the cluster.
Leonardo Collado-Torres
Rafael A. Irizarry, Martin Aryee, Hector Corrada Bravo, Kasper D. Hansen and Harris A. Jaffee. bumphunter: Bump Hunter. R package version 1.1.10.
calculatePvalues
## Preprocess the data
prep <- preprocessCoverage(genomeData,
cutoff = 0, scalefac = 32, chunksize = 1e3,
colsubset = NULL
)
## Get the F statistics
fstats <- genomeFstats
## Find the regions
regs <- findRegions(prep$position, fstats, "chr21", verbose = TRUE)
regs
## Not run:
## Once you have the regions you can proceed to annotate them
library("bumphunter")
genes <- annotateTranscripts(TxDb.Hsapiens.UCSC.hg19.knownGene::TxDb.Hsapiens.UCSC.hg19.knownGene)
annotation <- matchGenes(regs, genes)
annotation
## End(Not run)
# Find regions with smoothing the F-statistics by bumphunter::runmedByCluster
regs_smooth <- findRegions(prep$position, fstats, "chr21",
verbose = TRUE,
smoothFunction = bumphunter::runmedByCluster
)
## Compare against the object regs obtained earlier
regs_smooth
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