plotGrandLinear: Manhattan for GWAS

In tengfei/ggbio: Visualization tools for genomic data

Manhattan for GWAS

Description

A Manhattan plot is special scatter plot used to visualize data with a large number of data points, with a distribute of some higher-magnitude values. For example, in the GWAS(genome-wide association studies). Here we mainly focus on GWAS Manhattan plots. X-axis is genomic coordinates and Y-axis is negative logarithm of the associated P-value for each single nucleotide polymorphism. So higher the value, more stronger the association they are.

Usage

plotGrandLinear(obj, ..., facets, space.skip = 0.01, geom = NULL,
                 cutoff = NULL, cutoff.color = "red", cutoff.size = 1,
                 legend = FALSE, xlim, ylim, xlab, ylab, main,
                 highlight.gr = NULL, highlight.name = NULL,
                 highlight.col = "red", highlight.label = TRUE,
                 highlight.label.size = 5, highlight.label.offset =
                 0.05, highlight.label.col = "black", spaceline =
                 FALSE)

Arguments

obj	GRanges object which contains extra p value, before users pass this object, they need to make sure the pvalue has been changed to -log10(p).
...	extra arguments passed. such as color, size, alpha.
facets	facets formula, such as group ~ .
space.skip	numeric value for skip ratio, between chromosome spaces.default is 0.01.
geom	geometric object, defualt is "point".
cutoff	A numeric vector which used as cutoff for Manhattan plot.
cutoff.color	A character specifying the color used for cutoff. Default is "red".
cutoff.size	A numeric value which used as cutoff line size.
legend	A logical value indicate whether to show legend or not. Default is FALSE which disabled the legend.
xlim	limits for x scale.
ylim	limits for y scale.
xlab	Label for xscale.
ylab	Label for yscale.
main	title.
highlight.gr	a GRanges object, this wil highlight overlapped region with provided intervals.
highlight.name	if NULL, using rownames of GRanges object provided by argument highlight.gr, otherwise use character to indicate column used as labeled names.
highlight.col	highlight colors.
highlight.label	logical value, label the highlighted region of not.
highlight.label.size	highlight label size.
highlight.label.offset	highlight label offset.
highlight.label.col	highlight label color.
spaceline	show line between chromosomes.

Details

Please use seqlengths of the object and space.skip arguments to control the layout of the coordiant genome transformation.

aes(y = ...) is requried.

aes(color = ) is used to mapping to data variables, if just pass "color" without aes(), then will recycle the color to represent each chromosomes.please see the example below.

Value

Return a ggplot object.

Author(s)

Tengfei Yin

Examples

##  load
library(ggbio)
data(hg19IdeogramCyto, package = "biovizBase")
data(hg19Ideogram, package = "biovizBase")
library(GenomicRanges)

##  simul_gr
library(biovizBase)
gr <- GRanges(rep(c("chr1", "chr2"), each = 5),
              IRanges(start = rep(seq(1, 100, length = 5), times = 2),
                      width = 50))
autoplot(gr)

##  coord:genome
autoplot(gr, coord = "genome")
gr.t <- transformToGenome(gr)
head(gr.t)

##  is
is_coord_genome(gr.t)
metadata(gr.t)$coord


##  simul_snp
chrs <- as.character(levels(seqnames(hg19IdeogramCyto)))
seqlths <- seqlengths(hg19Ideogram)[chrs]
set.seed(1)
nchr <- length(chrs)
nsnps <- 100
gr.snp <- GRanges(rep(chrs,each=nsnps),
                  IRanges(start =
                          do.call(c, lapply(chrs, function(chr){
                            N <- seqlths[chr]
                            runif(nsnps,1,N)
                          })), width = 1),
                  SNP=sapply(1:(nchr*nsnps), function(x) paste("rs",x,sep='')),
                  pvalue =  -log10(runif(nchr*nsnps)),
                  group = sample(c("Normal", "Tumor"), size = nchr*nsnps,
                    replace = TRUE)
                  )

##  shorter
seqlengths(gr.snp)
nms <- seqnames(seqinfo(gr.snp))
nms.new <- gsub("chr", "", nms)
names(nms.new) <- nms
gr.snp <- renameSeqlevels(gr.snp, nms.new)
seqlengths(gr.snp)



##  unorder
autoplot(gr.snp, coord = "genome", geom = "point", aes(y = pvalue), space.skip = 0.01)

##  sort
gr.snp <- keepSeqlevels(gr.snp, c(1:22, "X", "Y"))
autoplot(gr.snp, coord = "genome", geom = "point", aes(y = pvalue), space.skip = 0.01)

##  with_seql
names(seqlths) <- gsub("chr", "", names(seqlths))
seqlengths(gr.snp) <- seqlths[names(seqlengths(gr.snp))]
autoplot(gr.snp, coord = "genome", geom = "point", aes(y = pvalue), space.skip = 0.01)

##  line
autoplot(gr.snp, coord = "genome", geom = "line", aes(y = pvalue, group = seqnames,
                                     color = seqnames))



##  plotGrandLinear
plotGrandLinear(gr.snp, aes(y = pvalue))

##  morecolor
plotGrandLinear(gr.snp, aes(y = pvalue, color = seqnames))
plotGrandLinear(gr.snp, aes(y = pvalue), color = c("green", "deepskyblue"))
plotGrandLinear(gr.snp, aes(y = pvalue), color = c("green", "deepskyblue", "red"))
plotGrandLinear(gr.snp, aes(y = pvalue), color = "red")

##  cutoff
plotGrandLinear(gr.snp, aes(y = pvalue), cutoff = 3, cutoff.color = "blue", cutoff.size = 4)

##  cutoff-low
plotGrandLinear(gr.snp, aes(y = pvalue)) + geom_hline(yintercept = 3, color = "blue", size = 4)

##  longer
## let's make a long name
nms <- seqnames(seqinfo(gr.snp))
nms.new <- paste("chr00000", nms, sep = "")
names(nms.new) <- nms
gr.snp <- renameSeqlevels(gr.snp, nms.new)
seqlengths(gr.snp)

##  rotate
plotGrandLinear(gr.snp, aes(y = pvalue)) + theme(axis.text.x=element_text(angle=-90, hjust=0))

##  sessionInfo
sessionInfo()

tengfei/ggbio documentation built on Nov. 5, 2023, 6:17 a.m.