ggbio (version 1.20.1)

geom_alignment: Alignment geoms for GRanges object

Description

Show interval data as alignment.

Usage

## S3 method for class 'GRanges':
geom_alignment(data, ..., xlab, ylab, main, facets = NULL, stat =
                 c("stepping", "identity"), range.geom = c("rect",
                 "arrowrect"), gap.geom = c("chevron", "arrow",
                 "segment"), rect.height = NULL, group.selfish = TRUE,
                  label = TRUE)
## S3 method for class 'TxDbOREnsDb':
geom_alignment(data, ..., which, columns = c("tx_id", "tx_name",
                 "gene_id"), names.expr = "tx_name", facets = NULL,
                 truncate.gaps = FALSE, truncate.fun = NULL, ratio =
                 0.0025)
## S3 method for class 'GRangesList':
geom_alignment(data, ..., which = NULL,
                          cds.rect.h = 0.25,
                          exon.rect.h = cds.rect.h,
                          utr.rect.h = cds.rect.h/2,
                          xlab, ylab, main,
                          facets = NULL, geom = "alignment",
                          stat = c("identity", "reduce"),
                          range.geom = "rect",
                          gap.geom = "arrow",
                          utr.geom = "rect",
                          names.expr = NULL,
                          label = TRUE,
                          label.color = "gray40",
                          arrow.rate = 0.015,
                          length = unit(0.1, "cm"))
## S3 method for class 'OrganismDb':
geom_alignment(data, ..., which,
                   columns = c("TXNAME", "SYMBOL", "TXID", "GENEID"),
                   names.expr = "SYMBOL",
                   facets = NULL,
                   truncate.gaps = FALSE,
                   truncate.fun = NULL, ratio = 0.0025
                   )

Arguments

data

A GRanges, data.frame, TxDb or EnsDb object.

...

Extra parameters such as aes() passed.

which

GRanges object to subset the TxDb or EnsDb object. For EnsDb: can also be a single, or a list of, filter object(s) extending BasicFilter-class.

cds.rect.h

cds heights.

exon.rect.h

exon heights.

utr.rect.h

utr heights.

label.color

label color.

arrow.rate

arrow rate.

length

arrow length.

columns

columns to get from object.

xlab

Label for x

ylab

Label for y

main

Title for plot.

facets

Faceting formula to use.

stat

For GRanges: Character vector specifying statistics to use. "stepping" with randomly assigned stepping levels as y varialbe. "identity" allow users to specify y value in aes.

For TxDb: defualt "identity" give full gene model and "reduce" for reduced model.

gap.geom

Geom for 'gap' computed from the data you passed based on the group information.

rect.height

Half height of the arrow body.

group.selfish

Passed to addStepping, control whether to show each group as unique level or not. If set to FALSE, if two groups are not overlapped with each other, they will probably be layout in the same level to save space.

truncate.gaps

logical value indicate to truncate gaps or not.

truncate.fun

shrinkage function. Please see shrinkagefun in package biovizBase.

ratio

used in maxGap.

geom

geometric object. only support "gene" now.

range.geom

geom for main intevals or exons.

utr.geom

geom for utr region.

names.expr

expression for showing y label.

label

logical value. Whether to label the intervals with names specified by argument names.expr.

Value

• A 'Layer'.

Examples

set.seed(1)
N <- 100
require(GenomicRanges)
## ======================================================================
##  simmulated GRanges
## ======================================================================
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))


## ======================================================================
##  default
## ======================================================================
ggplot(gr) + geom_alignment()
## or
ggplot() + geom_alignment(gr)

## ======================================================================
##  facetting and aesthetics
## ======================================================================
ggplot(gr) + geom_alignment(facets = sample ~ seqnames, aes(color = strand, fill = strand))

## ======================================================================
##  stat:stepping
## ======================================================================
ggplot(gr) + geom_alignment(stat = "stepping", aes(group = pair))

## ======================================================================
##  group.selfish controls when
## ======================================================================
ggplot(gr) + geom_alignment(stat = "stepping", aes(group = pair), group.selfish = FALSE)

## =======================================
##  main/gap geom
## =======================================
ggplot(gr) + geom_alignment(range.geom = "arrowrect", gap.geom = "chevron")

## =======================================
##  For TxDb
## =======================================
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
data(genesymbol, package = "biovizBase")
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
## made a track comparing full/reduce stat.
ggbio() + geom_alignment(data = txdb, which = genesymbol["RBM17"])
p1 <- ggplot(txdb) + geom_alignment(which = genesymbol["RBM17"])
p1
p2 <- ggplot(txdb) + geom_alignment(which = genesymbol["RBM17"], stat = "reduce")
tracks(full = p1, reduce = p2, heights = c(3, 1))
tracks(full = p1, reduce = p2, heights = c(3, 1)) + theme_tracks_sunset()
tracks(full = p1, reduce = p2, heights = c(3, 1)) +
     theme_tracks_sunset(axis.line.color = NA)
## change y labels
ggplot(txdb) + geom_alignment(which = genesymbol["RBM17"], names.expr = "tx_id:::gene_id")