ggbio

  • What is ggbio?
    • A programmable genome browser environment
  • Genome broswer concepts
    • A genome browser is a visulalization tool for plotting different types of genomic data in separate tracks along chromosomes.
    • The ggbio package (Yin et al., 2012) facilitates plotting of complex genome data objects, such as read alignments (SAM/BAM), genomic context/annotation information (gff/txdb), variant calls (VCF/BCF), and more. To easily compare these data sets, it extends the faceting facility of ggplot2 to genome browser-like tracks.
    • Most of the core object types for handling genomic data with R/Bioconductor are supported: GRanges, GAlignments, VCF, etc. For more details, see Table 1.1 of the ggbio vignette here.
    • ggbio’s convenience plotting function is autoplot. For more customizable plots, one can use the generic ggplot function.
    • Apart from the standard ggplot2 plotting components, ggbio defines serval new components useful for genomic data visualization. A detailed list is given in Table 1.2 of the vignette here.
    • Useful web sites:

Tracks: aligning plots along chromosomes

library(ggbio)
df1 <- data.frame(time = 1:100, score = sin((1:100)/20)*10)
p1 <- qplot(data = df1, x = time, y = score, geom = "line")
df2 <- data.frame(time = 30:120, score = sin((30:120)/20)*10, value = rnorm(120-30 +1))
p2 <- ggplot(data = df2, aes(x = time, y = score)) + geom_line() + geom_point(size = 2, aes(color = value))
tracks(time1 = p1, time2 = p2) + xlim(1, 40) + theme_tracks_sunset()

Plotting genomic ranges

GRanges objects are essential for storing alignment or annotation ranges in R/Bioconductor. The following creates a sample GRanges object and plots its content.

library(GenomicRanges)
set.seed(1); N <- 100; gr <- GRanges(seqnames = sample(c("chr1", "chr2", "chr3"), size = N, replace = TRUE), IRanges(start = sample(1:300, size = N, replace = TRUE), width = sample(70:75, size = N,replace = TRUE)), strand = sample(c("+", "-"), size = N, replace = TRUE), value = rnorm(N, 10, 3), score = rnorm(N, 100, 30), sample = sample(c("Normal", "Tumor"), size = N, replace = TRUE), pair = sample(letters, size = N, replace = TRUE))
autoplot(gr, aes(color = strand, fill = strand), facets = strand ~ seqnames)

Plotting coverage

autoplot(gr, aes(color = strand, fill = strand), facets = strand ~ seqnames, stat = "coverage")
## Scale for 'x' is already present. Adding another scale for 'x', which will replace the existing
## scale.

Mirrored coverage

pos <- sapply(coverage(gr[strand(gr)=="+"]), as.numeric)
pos <- data.frame(Chr=rep(names(pos), sapply(pos, length)), Strand=rep("+", length(unlist(pos))), Position=unlist(sapply(pos, function(x) 1:length(x))), Coverage=as.numeric(unlist(pos)))
neg <- sapply(coverage(gr[strand(gr)=="-"]), as.numeric)
neg <- data.frame(Chr=rep(names(neg), sapply(neg, length)), Strand=rep("-", length(unlist(neg))), Position=unlist(sapply(neg, function(x) 1:length(x))), Coverage=-as.numeric(unlist(neg)))
covdf <- rbind(pos, neg)
p <- ggplot(covdf, aes(Position, Coverage, fill=Strand)) + 
	    geom_bar(stat="identity", position="identity") + facet_wrap(~Chr)
p

Circular genome plots

ggplot(gr) + layout_circle(aes(fill = seqnames), geom = "rect")

More complex circular example

seqlengths(gr) <- c(400, 500, 700)
values(gr)$to.gr <- gr[sample(1:length(gr), size = length(gr))]
idx <- sample(1:length(gr), size = 50)
gr <- gr[idx]
ggplot() + layout_circle(gr, geom = "ideo", fill = "gray70", radius = 7, trackWidth = 3) +
  layout_circle(gr, geom = "bar", radius = 10, trackWidth = 4,
                aes(fill = score, y = score)) +
  layout_circle(gr, geom = "point", color = "red", radius = 14,
                trackWidth = 3, grid = TRUE, aes(y = score)) +
  layout_circle(gr, geom = "link", linked.to = "to.gr", radius = 6, trackWidth = 1)

Alignments and variants

To make the following example work, please download and unpack this data archive containing GFF, BAM and VCF sample files.

library(rtracklayer); library(GenomicFeatures); library(Rsamtools); library(GenomicAlignments); library(VariantAnnotation)
ga <- readGAlignments("./data/SRR064167.fastq.bam", use.names=TRUE, param=ScanBamParam(which=GRanges("Chr5", IRanges(4000, 8000))))
p1 <- autoplot(ga, geom = "rect")
p2 <- autoplot(ga, geom = "line", stat = "coverage")
vcf <- readVcf(file="data/varianttools_gnsap.vcf", genome="ATH1")
p3 <- autoplot(vcf[seqnames(vcf)=="Chr5"], type = "fixed") + xlim(4000, 8000) + theme(legend.position = "none", axis.text.y = element_blank(), axis.ticks.y=element_blank())
txdb <- makeTxDbFromGFF(file="./data/TAIR10_GFF3_trunc.gff", format="gff3")
p4 <- autoplot(txdb, which=GRanges("Chr5", IRanges(4000, 8000)), names.expr = "gene_id")
tracks(Reads=p1, Coverage=p2, Variant=p3, Transcripts=p4, heights = c(0.3, 0.2, 0.1, 0.35)) + ylab("")

Additional examples

See autoplot demo here

Additional genome graphics

Genome Browser: IGV

View genome data in IGV

  • Download and open IGV
  • Select in menu in top left corner A. thaliana (TAIR10)
  • Upload the following indexed/sorted Bam files with File -> Load from URL...
http://faculty.ucr.edu/~tgirke/HTML_Presentations/Manuals/Workshop_Dec_6_10_2012/Rrnaseq/results/SRR064154.fastq.bam
http://faculty.ucr.edu/~tgirke/HTML_Presentations/Manuals/Workshop_Dec_6_10_2012/Rrnaseq/results/SRR064155.fastq.bam
http://faculty.ucr.edu/~tgirke/HTML_Presentations/Manuals/Workshop_Dec_6_10_2012/Rrnaseq/results/SRR064166.fastq.bam
http://faculty.ucr.edu/~tgirke/HTML_Presentations/Manuals/Workshop_Dec_6_10_2012/Rrnaseq/results/SRR064167.fastq.bam
  • To view area of interest, enter its coordinates Chr1:49,457-51,457 in position menu on top.

For viewing BAM files in IGV as part of systemPipeR workflows.

  • systemPipeR: utilities for building NGS analysis pipelines
library("systemPipeR")
symLink2bam(sysargs=args, htmldir=c("~/.html/", "somedir/"), 
            urlbase="http://myserver.edu/~username/",
            urlfile="IGVurl.txt")

Controlling IGV from R

Note this may not work on all systems.

library(SRAdb)
startIGV("lm")
sock <- IGVsocket()
session <- IGVsession(files=myurls, 
                      sessionFile="session.xml", 
                      genome="A. thaliana (TAIR10)")
IGVload(sock, session)
IGVgoto(sock, 'Chr1:45296-47019')



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