R/qtl2ggplot Vignette

Whole Genome Allele Scan

Load example DO data from web. For convenience, we attach package ‘ggplot2’ for the autoplot function. Functions from ‘qtl2’ are explicitly referenced with prefix qtl2::.

library(qtl2ggplot)
library(ggplot2)

Download ‘qtl2’ cross2 object.

DOex <- 
  qtl2::read_cross2(
    file.path(
      "https://raw.githubusercontent.com/rqtl",
       "qtl2data/master/DOex",
       "DOex.zip"))

With multiple alleles, it is useful to examine an additive allele model. Download pre-calculated allele probabilities (~5 MB) as follows:

tmpfile <- tempfile()
file <- paste0("https://raw.githubusercontent.com/rqtl/",
               "qtl2data/master/DOex/DOex_alleleprobs.rds")
download.file(file, tmpfile)
apr <- readRDS(tmpfile)
unlink(tmpfile)

Alternatively, calculate these directly.

pr <- qtl2::calc_genoprob(DOex, error_prob=0.002)
apr <- qtl2::genoprob_to_alleleprob(pr)

Genome allele scan.

scan_apr <- qtl2::scan1(apr, DOex$pheno)

Summary of peaks.

qtl2::find_peaks(scan_apr, DOex$pmap)

##   lodindex       lodcolumn chr      pos       lod
## 1        1 OF_immobile_pct   2 96.84223 10.173313
## 2        1 OF_immobile_pct   3 15.02006  5.971503
## 3        1 OF_immobile_pct   X 74.57257  6.939151

New summary method:

summary(scan_apr, DOex$pmap)

## # A tibble: 3 × 5
##   pheno           chr     pos   lod marker            
##   <chr>           <fct> <dbl> <dbl> <chr>             
## 1 OF_immobile_pct 2      96.8 10.2  backupUNC020000070
## 2 OF_immobile_pct 3      15.0  5.97 backupUNC030729939
## 3 OF_immobile_pct X      74.6  6.94 UNC200000454

The basic plot of genome scan,

plot(scan_apr, DOex$pmap)

and the grammar of graphics (ggplot2) version.

autoplot(scan_apr, DOex$pmap)

Genome Allele Scan for Chr 2

Subset to chr 2.

DOex <- DOex[,"2"]
apr <- subset(apr, chr = "2")

scan_apr <- qtl2::scan1(apr, DOex$pheno)

qtl2::find_peaks(scan_apr, DOex$pmap)

##   lodindex       lodcolumn chr      pos      lod
## 1        1 OF_immobile_pct   2 96.84223 10.17331

plot(scan_apr, DOex$pmap)

autoplot(scan_apr, DOex$pmap)

coefs <- qtl2::scan1coef(apr, DOex$pheno)

summary(coefs, scan_apr, DOex$pmap)

## # A tibble: 1 × 14
##   pheno       chr     pos   lod marker     A     B     C     D     E     F     G
##   <chr>       <fct> <dbl> <dbl> <chr>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 OF_immobil… 2      96.8  10.2 backu… -6.93 -3.80 -6.27 -5.97 -30.1 -14.3 -3.87
## # … with 2 more variables: H <dbl>, intercept <dbl>

plot(coefs, DOex$pmap, 1:8, col = qtl2::CCcolors)

autoplot(coefs, DOex$pmap)

plot(coefs, DOex$pmap, 1:8, col = qtl2::CCcolors, scan1_output = scan_apr)

autoplot(coefs, DOex$pmap, scan1_output = scan_apr,
         legend.position = "none")

plot(coefs, DOex$pmap, c(5,8), col = qtl2::CCcolors[c(5,8)])

autoplot(coefs, DOex$pmap, c(5,8))

autoplot(coefs, DOex$pmap, c(5,8), facet = "geno")

plot(coefs, DOex$pmap, 4:5, col = qtl2::CCcolors[4:5], scan1_output = scan_apr)