## these are functions that I sometimes use in my code
## they are intended to be able to be run on any computer
## with R installed.
#################################
###
### Settings
###
#################################
options(stringsAsFactors=FALSE)
#################################
###
### Aliases for frequently used functions
###
#################################
s <- base::summary;
h <- utils::head;
n <- base::names;
as.dataframe<-base::data.frame;
#################################
###
### FUNCTION: sourceDir
###
#################################
# sources any *.R files in a given directory
#
# Args: path
# trace is a boolean to print file names as they are sourced
#
# Returns: nothing
#
# this function is copied from the "source" help text
#
sourceDir <- function(path, trace = TRUE, ...) {
for (nm in list.files(path, pattern = "\\.[Rr]$")) {
if(trace) cat(nm,":")
source(file.path(path, nm), ...)
if(trace) cat("\n")
}
}
#################################
###
### FUNCTION: write.txt
###
#################################
# write.table with my most frequently used settings
#
# Args:
# ... (vector of items to paste)
#
# Returns:
#
write.txt<-function (x, file="", quote=FALSE, sep="\t", row.names=FALSE, ...){
write.table(x, file, quote=quote, sep=sep, row.names=row.names, ...)
}
#################################
###
### FUNCTION: read.txt
###
#################################
# read.table with my most frequently used settings
#
# Args:
# ... (vector of items to paste)
#
# Returns:
# data frame
#
read.txt<-function (file="", sep="\t", header=TRUE,row.names=NULL, ...){
read.table(file, sep= sep, header= header, row.names= row.names, ...)
}
#################################
###
### FUNCTION: pasteNS
###
#################################
# Paste arguments with no spaces between them
#
# Args:
# ... (vector of items to paste)
#
# Returns:
# character vector result of paste
#
pasteNS<-function (...){
paste(..., sep="")
}
#################################
###
### FUNCTION: convertToComplement
###
#################################
# Converts string into its DNA complement
#
# Args:
# string
# fGenotype (boolean; if TRUE, orders the string alphabetically)
#
# Returns:
# string
#
convertToComplement<-function(x,fGenotype=TRUE){
allComps<-NULL
for (nucString in x){
bases=c("A","C","G","T")
xx<-unlist(strsplit(toupper(nucString),NULL))
thisComp=unlist(lapply(xx,function(bbb){
if(bbb=="A") compString<-"T"
if(bbb=="C") compString<-"G"
if(bbb=="G") compString<-"C"
if(bbb=="T") compString<-"A"
if(!bbb %in% bases) compString<-"N"
return(compString)
}))
if(fGenotype) thisComp = thisComp [order(thisComp)]
thisComp =paste(thisComp,collapse="")
allComps=c(allComps, thisComp)
}
return(allComps)
}
#################################
###
### FUNCTION: convertColsToNumeric
###
#################################
# Converts specified columns to numeric
#
# Args:
# data frame, column indices
#
# Returns:
# original DF with specified columns changed
#
convertColsToNumeric<-function(dfConv,colIndices){
for (i in colIndices){
dfConv[,i]=as.numeric(dfConv[,i])
}
return(dfConv)
}
#################################
###
### FUNCTION: printNumberedVector
###
#################################
#
# prints a vector to screen, one item per line with each line numbered
#
# Input: a vector
#
# Returns:
# nothing
#
##
printNumberedVector<-function(someVector){
cat(paste(1:length(someVector ), someVector,"\n"))
}
#################################
###
### FUNCTION: cnvSummary
###
#################################
#
# creates a summary of cnvs identified by the cnv-seq package
# writes the summary to a file
# returns the files
#
# Input: cnvFileName, outputFileName
#
# Returns:
# nothing
#
##
summarizeCNV<-function(cnvFileName,outputFileName){
## for testing
## cnvFileName ="*CNV.hits.log2-0.6.pvalue-0.001.minw-4.cnv"
if (! file.exists(outputFileName)) {
library(cnv)
cnvFileData <- read.delim(cnvFileName)
if (sum(cnvFileData $cnv!=0)){
cnvSummary<-NULL
for (i in seq(max(min(cnvFileData$cnv), 1), max(cnvFileData$cnv))) {
sub <- subset(cnvFileData, cnv == i)
start <- ceiling(mean(c(min(sub$start), min(sub$position))))
end <- floor(mean(c(max(sub$end), max(sub$position))))
cnvSummary <- rbind(cnvSummary ,c(paste("CNVR_", i, sep = ""), unique(sub$chromosome), start, end, end - start + 1, unique(sub$cnv.log2), unique(sub$cnv.p.value)))#, sep = "\t", file = file,
}
colnames(cnvSummary)= c("cnv", "chromosome", "start", "end", "size", "log2", "p.value")
cnvSummary=data.frame(cnvSummary)
for (i in 3:7){
cnvSummary[,i]=as.numeric(cnvSummary[,i])
}
} else {
return(NULL)
}
write.table(cnvSummary, outputFileName, row.names=FALSE, quote=FALSE, sep="\t")
} else {
cnvSummary =read.table(outputFileName, header=TRUE, sep="\t")
}
return(cnvSummary)
}
#################################
###
### FUNCTION: fixRowNamesColumn
###
#################################
#
# moves data in "Row.names" column to rownames
#
# Args: df
#
# Returns:
# dataframe
#
##
fixRowNamesColumn<-function(mergeResultsDF){
#mergeResultsDF= popByAgeWide
rownames(mergeResultsDF)= mergeResultsDF$Row.names
mergeResultsDF= mergeResultsDF[,2:ncol(mergeResultsDF)]
}
#################################
###
### FUNCTION: getLabelsAndMidPointsOfGroups
###
#################################
#
# useful for labeling axes and creating
#
# Args: df, valname, byname, passFUN, fnDesc
# Example Vals
# df= creatDF
# valname="creat"
# byname="breed"
# passFUN=length
# fnDesc="count"
# fReplaceValName=FALSE ## the default is to append
#
# Returns:
# dataframe
#
##
getLabelsAndMidPointsOfGroups<- function(charVec,alternatingColors=c("grey", "black")){
plotAnnotation<-data.frame(values= charVec)
previousVal= c("", charVec[1:(length(charVec )-1)])
switchPoint= charVec != previousVal
groupBreaks=data.frame(start=which(switchPoint))
groupBreaks$length= c(groupBreaks $start[2:nrow(groupBreaks)],length(charVec)+1)-groupBreaks$start
groupBreaks$end= groupBreaks$start+ (groupBreaks$length-1)
groupBreaks$midpoint=round(rowMeans(groupBreaks[,c("start","end")]),0)
groupBreaks$label= plotAnnotation$values[groupBreaks$midpoint]
groupBreaks$color= alternatingColors[1]
groupBreaks$color[ c(T,F) ]=alternatingColors[2]
plotAnnotation$color=as.character(unlist(apply(groupBreaks,1,function(x){
rep(x["color"],x["length"])
})))
plotAnnotation$labelnames= ""
plotAnnotation$labelnames[groupBreaks$midpoint]=plotAnnotation$value[groupBreaks$midpoint]
list(labelsDF=plotAnnotation, breaksDF=groupBreaks)
}
#################################
###
### FUNCTION: prettyAggregate
###
#################################
# wrapper for aggregate
# renames columns based on input
#
# Args: df, valname, byname, passFUN, fnDesc
# Example Vals
# df= creatDF
# valname="creat"
# byname="breed"
# passFUN=length
# fnDesc="count"
# fReplaceValName=FALSE ## the default is to append
#
# Returns:
# dataframe
#
##
prettyAggregate<-function(df, valname, byname, passFUN, fnDesc, fReplaceValName=FALSE){
if (fReplaceValName) {
agColName=fnDesc
} else {
agColName=pasteNS(valname,"_", fnDesc)
}
result=aggregate(df[, valname],by=list(df[, byname]), FUN= passFUN)
colnames(result)=c(byname, agColName)
return(result)
}
#################################
###
### FUNCTION: cbindList/rbindList
###
#################################
# tries to return a dataframe from a list of bind-able vectors or dataframes
# based on first example in Reduce help
#
# Args:
# List
#
# Returns:
# dataframe
#
##
cbindList <- function(x) Reduce("cbind", x)
rbindList <-function(x) Reduce("rbind",x)
#################################
###
### FUNCTION: bindRepeat
###
#################################
# returns a dataframe composed of n
# copies of the vector
# Args:
# vector2Rep - vector to be repeated
# n - times to repeat
## abandoned:
# fBindAsColumns - optional, boolean
#
# Returns:
# dataframe
#
##
bindRepeat <- function(vector2Rep,n){
a <- list()
for(i in 1:n) a[[i]] <- vector2Rep
rbindList(a)
}
#################################
###
### FUNCTION: inMB
###
#################################
# Convert a number of bases to megabases
#
# Args:
# number(s)
#
# Returns:
# vector
#
##
inMB<-function(bases){
bases/1000000
}
#################################
###
### FUNCTION: textListToVec
###
#################################
# Convert a chunk of text (one item per line) to a vector
# Just type textListToVec(" and then paste in the lines and type ")
#
# Args:
# newline-separated list
#
# Returns:
# vector
#
##
textListToVec <-function(a) strsplit(a,"\n")[[1]]
#################################
###
### FUNCTION: tableDF
###
#################################
# performs the table function
# but returns a well-formatted data.frame
#
# Args:
# valVector
#
# Returns:
# dataframe
#
##
tableDF<-function(valVector=c("a", "a", "b")){
t=data.frame(as.matrix(table(valVector)))
t2=data.frame(value=row.names(t), frequency=t[,1])
row.names(t2)=row.names(t)# colnames(t)=c("frequency")
return(t2)
}
#################################
###
### FUNCTION: interleave
###
#################################
# Interleave two vectorsAdd timestamp and data to plot
#
# Args:
# v1
# v2
#
# Returns:
# vector
#
##
interleave <- function(v1,v2)
{
ord1 <- 2*(1:length(v1))-1
ord2 <- 2*(1:length(v2))
c(v1,v2)[order(c(ord1,ord2))]
}
#################################
###
### FUNCTION: stampPlot
###
#################################
# Add timestamp and data to plot
#
# Args:
# desc.txt=""
# fOuter=FALSE
#
# Returns:
# nothinbg
#
##
stampPlot=function(desc.txt="",fOuter=FALSE ){
if(fOuter) {
pAdj=-2
} else {
pAdj=-0.6
}
mtext(paste(desc.txt, hbTimeStamp()),side=4,outer= fOuter,padj= pAdj,cex=.8)
}
#################################
###
### FUNCTION: snap
###
#################################
# like head, but also limits the number of columns. default is 6 columns 6 rows.
snap <-function (df,rowLim=6,colLim=6) {
# troubleshooting
#age=18:29
#height=runif(12,62,74)
#df =data.frame(age=age,height=height)
if (is(df)[1]=="data.frame" | is(df)[1]=="matrix"){
nrowDF =nrow(df)
ncolDF =ncol(df)
if (rowLim<nrowDF) nrowDF=rowLim
if (colLim<ncolDF) ncolDF=colLim
print(df[1:nrowDF,1:ncolDF])
} else {
print("cannot parse input")
}
}
#################################
###
### FUNCTION: getAllListSubItemsByIndex
###
#################################
# get the nth sub item from each item
#
# Args:
# theList, list to pull from
# theIndex, the index of desired items
#
# Returns:
# vector or results
#
getAllListSubItemsByIndex <-function (theList, theIndex){
paste(lapply(theList,function(x) x=x[[theIndex]]))
}
#################################
###
### FUNCTION: greaterOf
###
#################################
# get the greater of two items
#
# Args:
# values to compare
#
# Returns:
# greater value
#
greaterOf <- function (x,y) {
if (x>y | y==x){
x
} else {
if (y>x) {
y
} else {
NA
}
}
}
#################################
###
### FUNCTION: lesserOf
###
#################################
# get the lesser of two items
#
# Args:
# values to compare
#
# Returns:
# lesser value
#
lesserOf <- function (x,y) {
if (x<y | y==x ){
x
} else {
if (y<x) {
y
} else {
NA
}
}
}
### FUNCTION: isBetween
###
#################################
# is one value between two others
#
# Args:
# 3 values
#
# Returns:
# TRUE or FALSE
#
isBetween <- function (x,y,z) {
x>y & x<z
}
#################################
###
### FUNCTION: initialCap
###
#################################
# Converts each string in a vector to initial upper case
#
# Args:
# wordsToConvert: vector of genes symbols
#
# Returns:
# vector with changed words
#
initialCap <- function(wordsToConvert) {
return_list<-NULL
for (i in 1:length(wordsToConvert)){
r<-tolower(wordsToConvert[i])
s <- strsplit(r, " ")[[1]]
return_list[i]=paste(toupper(substring(s, 1,1)), substring(s, 2), sep="", collapse=" ")
}
return(return_list)
}
#################################
###
### FUNCTION: allIdentical
###
#################################
# tests whether each item in a vector is identical
#
# Args:
# vectorToTest: vector
#
# Returns:
# TRUE or FALSE
#
allIdentical <- function(vectorToTest){
sum(! vectorToTest %in% vectorToTest[1])}
#################################
###
### FUNCTION: set_up_plot
###
#################################
# Determines axis values from data
# adds a time stamp
#
# Args:
# x & y data
# fPlotFromZero
# fPlotEvenAxes
# Returns:
# plot
#
set_up_plot <-function(x,y,fPlotFromZero=TRUE, fPlotEvenAxes=FALSE,fDateStamp=TRUE,stampText="",fOuter=FALSE,xAxLabel=colnames(x), yAxLabel=colnames(y), ...){
#print(names(x))
# if
# xAxName=colnames(x)
# yAxLabel=colnames(y)
if(fPlotEvenAxes){
x=c(min(c(x,y)),max(c(x,y)))
y=x
}
if (fPlotFromZero) {
plot_y_min=0
plot_x_min=0
} else {
plot_y_min=min(y)
plot_x_min=min(x)
}
plot_y_max=max(y)
plot_x_max=max(x)
plot(c(plot_x_min, plot_x_max),c(plot_y_min, plot_y_max), xlab= xAxLabel , ylab= yAxLabel , type="n", ... )
if (fDateStamp) stampPlot(stampText,fOuter= fOuter)
}
#################################
###
### FUNCTION: hbTimeStamp
###
#################################
# Get formatted time and date
#
# Args (all optional):
# sepYMD
# sepHMS
# sepDateTime
# Returns:
# character vector
#
hbTimeStamp<-function(sepYMD="-", sepHMS=".", sepDateTime="_", dateVars=c("Y","m","d"), timeVars=c("I", "M", "S")){
dateSpec=paste(paste("%", dateVars, sep=""), collapse= sepYMD)
timeSpec=paste(paste("%", timeVars, sep=""), collapse= sepHMS)
paste(format(Sys.time(), dateSpec),paste(format(Sys.time(), timeSpec),substring(format(Sys.time(), "%r"),10,11),sep=""),sep= sepDateTime)
}
#################################
###
### FUNCTION: breakPlotIntoPages
###
#################################
# Breaks data into page-size chunks and calls a plotting function for each chunk
#
# Args:
# dataframe with plot data
# optional: desired rows per page
# Returns:
# multiple plots
#
breakPlotIntoPages<-function(multipagePlotData,rowsPerPage=40,varList){
#if (! "myPlot" %in% varList) {
# print("the 'myPlot' function must exist")
# return()
# }
plotRows=nrow(multipagePlotData)
dataBreaks=unique(c(seq(from=1,to=plotRows,by=rowsPerPage),plotRows))
breakCount=length(dataBreaks)
penultimateBreakCount= breakCount-1
lastPageRowCount= dataBreaks[breakCount ]-dataBreaks[penultimateBreakCount]
for (i in 1:(length(dataBreaks)-1)){
brokenData=multipagePlotData[dataBreaks[i]:dataBreaks[i+1],]
xLimVals=c(0,rowsPerPage*1.6)
barPos=myPlot(brokenData,xLimVals,1)
}
}
## a useful function: rev() for strings
strReverse <- function(x)
sapply(lapply(strsplit(x, NULL), rev), paste, collapse="")
##strReverse(c("abc", "Statistics"))
#make transparenbt
################################
##
## FUNCTION: makeTransparent
##
################################
#Add transparency to colors
# Args:
# vector of colors in name or hex format, e.g. grey or #FFCDFF
# desiredPctTranparent
# Returns:
# same colors with transparency added
#
makeTransparent<-function(colorVector=c("#FFCDFF", "#C0108C", "#CB7600"), desiredPctTranparent=50){
#colorVector=c("grey", "blue")
if (substr(colorVector[1],0,1)!="#") {
colorVector =rgb(t(col2rgb(colorVector)/255))
}
s=seq(0,255,length.out=21)
transparencyCodes=data.frame(pctTransparent=100*(1-(s/255)))
t2=unlist(lapply(s,function(x) rgb(0,100,0,x,maxColorValue=255)))
transparencyCodes$hexSuffix= substring(t2,8,9)
paste(rgb(t(col2rgb(colorVector)),maxColorValue=255), transparencyCodes[transparencyCodes$pctTransparent== as.character(desiredPctTranparent),2],sep="")
}
#################################
###
### FUNCTION: plotMultipleCors
###
#################################
# Plots multiple vectors against
# a single vector and returns
# correlations
#
# Args:
# plotData
## plot data should have x values in first col, and any number of cols after that can be Y
## column names determine legend text
# vColors -- a vector of colors the length of each Y col in plotData
# ylabText -- text for Y label
# legendPos -- legend position, like "topleft"
# fNormalizeY -- normalize each Y value so the max val is 100
# Returns:
# plot
#
plotMultipleCors <-function(plotData, vColors="",ylabText="", xlabText ="Breed average creatinine level",legendPos="topleft",fNormalizeY=TRUE,...){
## plot data should have x values in first col, and any number of cols after that can be Y
#test plotData= gAcdDesc[,c("mean","se","sd","Height","Weight")]
library(plotrix)
x= plotData[,1]
if (fNormalizeY) {
plotData[,2:ncol(plotData)]=apply(plotData[,2:ncol(plotData)],2,function(y){
# 100*y/max(y)
rescale(y,c(0,100))
})
}
maxY=max(plotData[,2:ncol(plotData)],na.rm=TRUE)
set_up_plot( x,0: maxY,xAxLabel= xlabText, yAxLabel=ylabText ,...)
# if (vColors =""){
nColorsNeeded= ncol(plotData)-1
pal1=brewer.pal(8,"Set1")
vColors=pal1[rep(1:length(pal1), nColorsNeeded)[1: nColorsNeeded]]
# }
plotSettings=data.frame(dataName =colnames(plotData[,2:ncol(plotData)]),color= vColors)
plotSettings$notNA=apply(plotData[,2:ncol(plotData)],2,function(x){
sum(!is.na(x))
})
plotSettings$legendText= plotSettings$dataName
plotSettings$pch=0:(nrow(plotSettings)-1)
for (i in 1:nrow(plotSettings)){
y=plotData[,(i+1)]
points(x,y,col= plotSettings$color[i],pch=plotSettings$pch[i])
abline(lm(y ~ x),col= plotSettings$color[i])
rsq <-cor(x,y, use="complete.obs")
plotSettings$corr_value[i] <- format(c(rsq, 0.123456789), digits=2)[1]
##text(mean(x),mean(y),substitute(paste("R"^{2}, " = "*x),list(x= corr_value) ),cex=1,col= vColors[i-1])
##legend(210, 110, bquote(r^2 ==.(format(summary(regression)$adj.r.squared,digits=3))))
print(plotSettings$color[i])
} #end for loop
legend(legendPos, legend=pasteNS(plotSettings$legendText,", Rsq=",plotSettings$corr_value, ", n=",plotSettings$notNA), pch= plotSettings$pch, col= plotSettings$color)
# colnames(plotData[,2:ncol(plotData)]), lty=1, col=vColors)
} ## end function
#################################
###
### FUNCTION: plotCors
###
#################################
# Plots multiple vectors against
# a single vector and returns
# correlations
#
# Args:
# plotData
## plot data should have x values in first col, and any number of cols after that can be Y
## column names determine legend text
# vColors -- a vector of colors the length of each Y col in plotData
# ylabText -- text for Y label
# legendPos -- legend position, like "topleft"
# fNormalizeY -- normalize each Y value so the max val is 100
# Returns:
# plot
#
plotCors<-function(plotData, vColors="",ylabText=colnames(plotData)[2], xlabText =colnames(plotData)[1],legendPos="topleft",fNormalizeY=TRUE,...){
## plot data should have x values in first col, and any number of cols after that can be Y
#test plotData= gAcdDesc[,c("mean","se","sd","Height","Weight")]
#plotData=na.omit(plotData)
x= plotData[,1]
if (fNormalizeY) {
plotData[,2]=100*plotData[,2]/max(plotData[,2])
}
y=plotData[,2]
set_up_plot( x,y,xAxLabel= xlabText, yAxLabel=ylabText ,...)
points(x,y)#,col= plotSettings$color[i])
abline(lm(y ~ x)) #,col= plotSettings$color[i])
rsq <-cor(x,y, use="complete.obs")
rsqTxt <- format(c(rsq, 0.123456789), digits=2)[1]
##text(mean(x),mean(y),substitute(paste("R"^{2}, " = "*x),list(x= corr_value) ),cex=1,col= vColors[i-1])
##legend(210, 110, bquote(r^2 ==.(format(summary(regression)$adj.r.squared,digits=3))))
#print(plotSettings$color[i])
title(sub=pasteNS("Rsq=", rsqTxt ))
# colnames(plotData[,colSpec]), lty=1, col=vColors)
} ## end function
#################################
###
### FUNCTION: groupSNPsIntoLoci
###
#################################
#
# find groups of nearby SNPs
#
# Args:
# hitListSnpChrID any kind of chromosome identifier
# hitListSnpPos position of snp, either a number of a snp id like chr15.44226659
# maxInterSNPRange the maximum acceptable distance between SNPs
#
# Returns:
# data.frame vector result of paste
# data frame contains columns - c("chr", "minPos", "maxPos", "minPVal", "snpCount", "locID", "locusSize")
#
# find windows in snps
groupSNPsIntoLoci<-function(hitListSnpChrID, hitListSnpPos, hitListSnpPVals, maxInterSNPRange=1E6){
#test hitListSnpChrID=
# hitListSnpChrID =KCsize_candidates$chrChar
# hitListSnpPos=KCsize_candidates$pos
# hitListSnpPVals=KCsize_candidates$KC.LOGP
if (sum(grepl("chr", hitListSnpPos))>1){
hitListSnpPos=as.numeric(gsub("^[^\\.]*\\.","", hitListSnpPos))
}
hitList=data.frame(cbind(hitListSnpChrID, hitListSnpPos, hitListSnpPVals))
colnames(hitList)=c("chr","pos","pval")
hitList$pos=as.numeric(hitList$pos)
hitList$pval =as.numeric(hitList$pval)
# set up variables and record info for first row
#assocLocus columns: chr, minPos, minPos, minPVal, snpCount
assocLocus<-NULL
hitList= hitList[order(hitList$chr, hitList$pos),]
currAssocLocus= data.frame(c(hitList[1,c("chr","pos","pos","pval")]))
colnames(currAssocLocus)=c("chr", "minPos", "maxPos", "minPVal")
currAssocLocus$snpCount[1]=1
#round(hitList[1,"pos"]/1E6,0)
hitList$locusID=NA
currAssocLocus$locID[1]=pasteNS(hitList[1,"chr"],".",round(hitList[1,"pos"]/1E6,0),"Mb")
for (i in 2:nrow(hitList)){
# check each snp
if (hitList[i,"chr"]==currAssocLocus$chr[1] & (abs(hitList[i,"pos"]-currAssocLocus$minPos[1])<maxInterSNPRange | abs(hitList[i,"pos"]-currAssocLocus$minPos[1])<maxInterSNPRange)){
# they are on the same chromosome and within maxInterSNPRange of each other
# extend the current Association Locus values (update currAssocLocus)
currAssocLocus$snpCount[1]=currAssocLocus$snpCount[1]+1
if (hitList[i,"pval"]<currAssocLocus$minPVal[1]) currAssocLocus$minPVal[1]=hitList[i,"pval"]
if (hitList[i,"pos"]<currAssocLocus$minPos[1]) currAssocLocus$minPos[1]=hitList[i,"pos"]
if (hitList[i,"pos"]>currAssocLocus$maxPos[1]) currAssocLocus$maxPos[1]=hitList[i,"pos"]
if (i==nrow(hitList)) assocLocus<-rbind(assocLocus, currAssocLocus) ## add this last locus to the list
} else {
assocLocus<-rbind(assocLocus, currAssocLocus)
currAssocLocus[1,c("chr", "minPos", "maxPos", "minPVal")]=c(hitList[i,c("chr","pos","pos","pval")])
currAssocLocus$snpCount[1]=1
currAssocLocus$locID[1]=pasteNS(hitList[i,"chr"],".",round(hitList[i,"pos"]/1E6,0),"Mb")
}
hitList$locusID[i]=currAssocLocus$locID[1]
}
assocLocus=data.frame(assocLocus)
assocLocus$locusSize= assocLocus$maxPos-assocLocus$minPos+1
return(assocLocus)
}