neqtl: Smoothed count of traits mapping to positions across genome

Description Usage Arguments Value Author(s) See Also Examples

Description

Counts the number of positions within a window centered at a position on a chromosome.

Given a list of positions of significant LOD scores, counts the number of traits with significant maximum LOD scores at a given set of positions along the genome

Usage

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neqtl(sigpos.out, chr, pos, win = 5, inc = 0.2)

Arguments

sigpos.out

Output from maxlod.sigpos function, a list of positions of significant maximum LOD scores

Any list made up of a vector of positions for each chromosome.

chr

Vector of chromosomes (as a factor) for count, corresponding to pos, e.g. first column of scanone object

pos

Vector of positions for count, corresponding to chr, e.g. second column of scanone object

win

Numeric value of window size, count will be number of traits with significant maximum LOD score within the window, centered at c(chr,pos)

inc

Numeric value of step increment between positions, default is 0.2

Value

scanone object with cbind(chr,pos) as the first two columns, and number of transcripts with significant maximum LOD score in the pheno column

Author(s)

Karl W. Broman and Aimee Teo Broman

See Also

scanone plot.scanone

Examples

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data(fake.f2expr)
fake.f2expr <- calc.genoprob(fake.f2expr)

## pheno.col=1:nphe(fake.f2expr) takes awhile ##
scan.f2 <- scanone(fake.f2expr,pheno.col=1:100, method="hk")
maxlod.f2 <- maxlod(scan.f2)
sigpos.f2 <- maxlod.sigpos(maxlod.f2,sig.lod=3)

n.f2 <-neqtl(sigpos.f2,chr=scan.f2[,1],pos=scan.f2[,2])
plot(n.f2)

atbroman/neqtl documentation built on May 10, 2019, 2:08 p.m.