findFocals: findFocals

In bernatgel/FindFocals: Find focal gains & deletions in SNP array data

Description

Find clusters of extrem LRR values and determine if they might be classified as a focal gain or deletion.

Usage

findFocals(snps, sample.name, ignore.chr.Y=NULL, min.snps.in.cluster=5, max.extension=6,
fdel.sd.lim=4, fdel.min.num.below.thr=6, fdel.min.pct.below.thr=0.3, fdel.max.pct.above.mean=0.1,
fgain.sd.lim=3.5, fgain.min.num.above.thr=6, fgain.min.pct.above.thr=0.4, fgain.max.pct.below.mean=0.2,
cbs.min.segment.length=2e6, cbs.alpha=0.01, verbose=TRUE)

Arguments

snps	The SNPs data
sample.name	The name of the sample
ignore.chr.Y	(defaults to NULL)
min.snps.in.cluster	(defaults to 5)
max.extension	(defaults to 6)
fdel.sd.lim	(defaults to 4)
fdel.min.num.below.thr	(defaults to 6)
fdel.min.pct.below.thr	(defaults to 0.3)
fdel.max.pct.above.mean	(defaults to 0.1)
fgain.sd.lim	(defaults to 3.5)
fgain.min.num.above.thr	(defaults to 6)
fgain.min.pct.above.thr	(defaults to 0.4)
fgain.max.pct.below.mean	(defaults to 0.2)
cbs.min.segment.length	(defaults to 2e6)
cbs.alpha	(defaults to 0.01)
verbose	(defaults to TRUE)

Details

Given a GRanges with SNP data as the one created by loadSNPData, it processess the LRR values to detect clusters of outliers, that is, clusters of SNP a number of standard deviations above or below the mean LRR. Once detected, it will try to extend the detected clusters until the addition of a new SNP fails to comply with the required thresholds.

Value

A "FindFocalsResults" object with the results of the analysis. The object is a list with the results for gains and deletions in different slots.

bernatgel/FindFocals documentation built on May 3, 2019, 9:04 p.m.