typos

.gitignore

@@ -5,3 +5,4 @@ vagrantDNA/.Rproj.user*/*
 .Rproj.user
 vagrantDNA.Rcheck
 *zarr
+

vagrantDNA/DESCRIPTION

@@ -1,7 +1,7 @@
 Package: vagrantDNA
 Type: Package
 Title: Estimating the proportion of vagrant DNA in a genome
-Version: 1.1.0
+Version: 1.1.1
 Author: Richard Nichols and Hannes Becher
 Maintainer: The package maintainer <[email protected]>
 Description: The package two functions rainbowPlot and divEst. They produce two different estimates of the proportion of DNA from a particular vagrant genome. They exploit low coverge data from multiple individuals in which the vagrant DNA has taken residence (see Becher and Nichols 2022).

vagrantDNA/R/Rainbow_Plot.R

@@ -82,12 +82,13 @@
 #' ## plot and printout (by default) the results of running rainbowPlot on the parrot data.
 #' rainbowPlot(parrotDF, seed = 12345, title = "Parrot")
 #' ##
-#' ## plot without printing the results and store results in res1.
-#' res1 <- rainbowPlot(parrotDF, seed = 12345, printout = FALSE, title = "Parrot")
-#' ## print just the stored estimates (the first two elements of the list)
-#' print(res1[1:2])
-#' ## Inspect the residuals of the lmer model
-#' plot(res1$lmer.model)
+#' ## plot without printing the results and store results in parrotFit
+#' parrotFit <- rainbowPlot(parrotDF, seed = 12345, printout = FALSE, title = "Parrot")
+#' ## Inspect relationship between intercepts and SNP location
+#' interceptPositionPlot(parrotFit)
+#' ## Inspect mapping depth of nuclear insert allele across samples
+#' selAllPlot(parrotDF, parrotFit)
+#'
 #' @export
 rainbowPlot <- function(data,
                       nloci = 400,
@@ -322,7 +323,7 @@ rainbowPlot <- function(data,
   if (printout) {
     cat('Intercept based on ', numgoodloci, 'SNP loci \n')
     cat('Estimate: ', signif(intercepts[1],3), '\n')
-    cat('Confindence Interval: ',
+    cat('Confidence Interval: ',
                 signif(intercepts[2],3),
                 '-',
                 signif(intercepts[3],3),

vagrantDNA/R/selAllPlot.R

@@ -16,21 +16,23 @@
 #'  selAllPlot(humanDF) # overall alt allele counts
 #'  selAllPlot(humanDF, humanFit) # alt allele count at loci selected for fit
 #'  }
-selAllPlot <- function(dd,ff,ylim=c(0, 10),...){
+selAllPlot <- function(dd,ff,ylim=c(0, 10),ylab="Allele count",...){
   if(hasArg(ff)){
     posString <- rownames(coef(summary(ff$lmer.model)))
     sites <- substr(posString, 9, 20)
     pDat <- dd[dd$Position %in% sites,]
     boxplot(pDat$DP * exp(pDat$ylog) ~ pDat$Sample,
             main="Alt. allele count at selected loci",
             ylim=ylim,
+            ylab=ylab,
             ...)
     goodDatMeds <- round(as.numeric(tapply(pDat$DP * exp(pDat$ylog), pDat$Sample, function(x) boxplot.stats(x)$stats[3])))
     if(sum(goodDatMeds < 2) > length(goodDatMeds)/2) warning("The majority of individuals have a median alternate allele depth of 1. This suggests that vagrant DNA proportion or the sequencing depth may be insufficient for an accurate estimate. Consider using more WGS data if possible.")
   } else {
     boxplot(dd$DP * exp(dd$ylog) ~ dd$Sample,
             main="Alt. allele count at all loci",
             ylim=ylim,
+            ylab=ylab,
             ...)
     cat("Plot shows alt allels counts for all loci. Supply rainbowPlot object to show only selected loci.\n")
     goodDatMeds <- round(as.numeric(tapply(dd$DP * exp(dd$ylog), dd$Sample, function(x) boxplot.stats(x)$stats[3])))