asplot {gap}

Regional association plot

Description

Regional association plot

Usage

asplot(
  locus,
  map,
  genes,
  flanking = 1000,
  best.pval = NULL,
  sf = c(4, 4),
  logpmax = 10,
  pch = 21
)

Arguments

locus

Data frame with columns c("CHR", "POS", "NAME", "PVAL", "RSQR") containing association results.

map

Genetic map, i.e, c("POS","THETA","DIST").

genes

Gene annotation with columns c("START", "STOP", "STRAND", "GENE").

flanking

Flanking length.

best.pval

Best p value for the locus of interest.

sf

scale factors for p values and recombination rates, smaller values are necessary for gene dense regions.

logpmax

Maximum value for -log10(p).

pch

Plotting character for the SNPs to be highlighted, e.g., 21 and 23 refer to circle and diamond.

Details

This function obtains regional association plot for a particular locus, based on the information about recombinatino rates, linkage disequilibria between the SNP of interest and neighbouring ones, and single-point association tests p values.

Note that the best p value is not necessarily within locus in the original design.

Author(s)

Paul de Bakker, Jing Hua Zhao, Shengxu Li

References

Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H, Roix JJ, Kathiresan S, Hirschhorn JN, Daly MJ, Hughes TE, Groop L, Altshuler D, Almgren P, Florez JC, Meyer J, Ardlie K, Bengtsson Boström K, Isomaa B, Lettre G, Lindblad U, Lyon HN, Melander O, Newton-Cheh C, Nilsson P, Orho-Melander M, Råstam L, Speliotes EK, Taskinen MR, Tuomi T, Guiducci C, Berglund A, Carlson J, Gianniny L, Hackett R, Hall L, Holmkvist J, Laurila E, Sjögren M, Sterner M, Surti A, Svensson M, Svensson M, Tewhey R, Blumenstiel B, Parkin M, Defelice M, Barry R, Brodeur W, Camarata J, Chia N, Fava M, Gibbons J, Handsaker B, Healy C, Nguyen K, Gates C, Sougnez C, Gage D, Nizzari M, Gabriel SB, Chirn GW, Ma Q, Parikh H, Richardson D, Ricke D, Purcell S (2007). “Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels.” Science, 316(5829), 1331-6. ISSN 0036-8075, doi:10.1126/science.1142358.

Examples

## Not run: 
require(gap.datasets)
asplot(CDKNlocus, CDKNmap, CDKNgenes)
title("CDKN2A/CDKN2B Region")
asplot(CDKNlocus, CDKNmap, CDKNgenes, best.pval=5.4e-8, sf=c(3,6))

## NCBI2R

options(stringsAsFactors=FALSE)
p <- with(CDKNlocus,data.frame(SNP=NAME,PVAL))
hit <- subset(p,PVAL==min(PVAL,na.rm=TRUE))$SNP

library(NCBI2R)
# LD under build 36
chr_pos <- GetSNPInfo(with(p,SNP))[c("chr","chrpos")]
l <- with(chr_pos,min(as.numeric(chrpos),na.rm=TRUE))
u <- with(chr_pos,max(as.numeric(chrpos),na.rm=TRUE))
LD <- with(chr_pos,GetLDInfo(unique(chr),l,u))
# We have complaints; a possibility is to get around with 
# https://ftp.ncbi.nlm.nih.gov/hapmap/
hit_LD <- subset(LD,SNPA==hit)
hit_LD <- within(hit_LD,{RSQR=r2})
info <- GetSNPInfo(p$SNP)
haldane <- function(x) 0.5*(1-exp(-2*x))
locus <- with(info, data.frame(CHR=chr,POS=chrpos,NAME=marker,
                    DIST=(chrpos-min(chrpos))/1000000,
                    THETA=haldane((chrpos-min(chrpos))/100000000)))
locus <- merge.data.frame(locus,hit_LD,by.x="NAME",by.y="SNPB",all=TRUE)
locus <- merge.data.frame(locus,p,by.x="NAME",by.y="SNP",all=TRUE)
locus <- subset(locus,!is.na(POS))
ann <- AnnotateSNPList(p$SNP)
genes <- with(ann,data.frame(ID=locusID,CLASS=fxn_class,PATH=pathways,
                             START=GeneLowPoint,STOP=GeneHighPoint,
                             STRAND=ori,GENE=genesymbol,BUILD=build,CYTO=cyto))
attach(genes)
ugenes <- unique(GENE)
ustart <- as.vector(as.table(by(START,GENE,min))[ugenes])
ustop <- as.vector(as.table(by(STOP,GENE,max))[ugenes])
ustrand <- as.vector(as.table(by(as.character(STRAND),GENE,max))[ugenes])
detach(genes)
genes <- data.frame(START=ustart,STOP=ustop,STRAND=ustrand,GENE=ugenes)
genes <- subset(genes,START!=0)
rm(l,u,ugenes,ustart,ustop,ustrand)
# Assume we have the latest map as in CDKNmap
asplot(locus,CDKNmap,genes)

## End(Not run)