geom_alignment-method: Alignment geoms for GRanges object
In ggbio: Visualization tools for genomic data

Description Usage Arguments Value Author(s) Examples

Show interval data as alignment.

## S4 method for signature '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)

## S4 method for signature '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)

## S4 method for signature '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",
                          label.size = 3,
                          arrow.rate = 0.015,
                          length = unit(0.1, "cm"))

## S4 method for signature '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
                   )

`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 object extending `AnnotationFilter`, an `AnnotationFilterList` combining such objects or a filter expression in form of a `formula`.
`cds.rect.h`	cds heights.
`exon.rect.h`	exon heights.
`utr.rect.h`	utr heights.
`label.color`	label color.
`label.size`	label size.
`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`.

A 'Layer'.

Tengfei Yin

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")