tricubeStat: Calculate tricube weighted statistics for each SNP

In bmansfeld/QTLseqr: QTL mapping using Bulk Segregant Analysis of Next Generation Sequencing data.

Description

Uses local regression (wrapper for locfit) to predict a tricube smoothed version of the statistic supplied for each SNP. This works as a weighted average across neighboring SNPs that accounts for Linkage disequilibrium (LD) while minizing noise attributed to SNP calling errors. Values for neighboring SNPs within the window are weighted by physical distance from the focal SNP.

Usage

tricubeStat(POS, Stat, windowSize = 2e+06, ...)

Arguments

POS	A vector of genomic positions for each SNP
Stat	A vector of values for a given statistic for each SNP
...	Other arguments passed to locfit and subsequently to locfit.raw() (or the lfproc). Usefull in cases where you get "out of vertex space warnings"; Set the maxk higher than the default 100. See locfit.raw().
WinSize	the window size (in base pairs) bracketing each SNP for which to calculate the statitics. Magwene et. al recommend a window size of ~25 cM, but also recommend optionally trying several window sizes to test if peaks are over- or undersmoothed.

Value

Returns a vector of the weighted statistic caluculted with a tricube smoothing kernel

See Also

getG for G statistic calculation

locfit for local regression

Examples

df_filt_4mb$Gprime <- tricubeStat(POS, Stat = GStat, WinSize = 4e6)

bmansfeld/QTLseqr documentation built on Jan. 24, 2020, 3:56 p.m.