create 3d Geometry by given genomic signals

Create a 3d Geometry by given genomic signals for target 3d positions.

create3dGenomicSignals(
  GenoSig,
  targetObj,
  signalTransformFun,
  positionTransformFun,
  genomicScoreRange,
  reverseGenomicSigs,
  type = "segment",
  tag,
  name,
  color = c("gray30", "darkred"),
  rotation = c(0, 0, 0),
  ...
)

Arguments

GenoSig

The Genomic signals. An object of GRanges, Pairs, or GInteractions with scores or an object of track.

targetObj

The GRanges object with mcols x0, y0, z0, x1, y1, and z1

signalTransformFun

The transformation function for genomic signals.

positionTransformFun

The transformation function for the coordinates. The function must have input as a data.frame with colnames x0, y0, z0, x1, y1, and z1. And it must have output as same dimension data.frame.

genomicScoreRange

The genomic signals range.

reverseGenomicSigs

Plot the genomic signals in reverse values.

type

The Geometry type.See threeJsGeometry

tag

The tag used to group geometries.

name

The prefix for the name of the geometries.

color

The color of the signal. If there is metadata 'color' in GenoSig this parameter will be ignored.

rotation

The rotations in the x, y and z axis in radians.

...

the parameters for each different type of geometries. If type is 'segments', lwd.maxGenomicSigs (the maximal lwd of the line) is required. If type is 'circle', radius (the radius of the circle) and the maxVal (the value for 2*pi) is required. If type is 'sphere', 'dodecahedron', 'icosahedron', 'octahedron', or 'tetrahedron', radius is required. If type is 'box', 'capsule', 'cylinder', 'cone', or 'torus', if the properties of correspond geometry is not set, they will be set to the transformed score value. If type is 'json', please refer the documentation about BufferGeometryLoader at threejs.org If input 'GenoSig' is an object of Pairs or GInteractions, the type will be set to 'polygon' and topN is used to set how many top events will be plot.

Value

threeJsGeometry objects or NULL

Examples

library(GenomicRanges)
#> Loading required package: stats4
#> Loading required package: BiocGenerics
#> Loading required package: generics
#> 
#> Attaching package: 'generics'
#> The following objects are masked from 'package:base':
#> 
#>     as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
#>     setequal, union
#> 
#> Attaching package: 'BiocGenerics'
#> The following objects are masked from 'package:stats':
#> 
#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from 'package:base':
#> 
#>     Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#>     as.data.frame, basename, cbind, colnames, dirname, do.call,
#>     duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
#>     mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
#>     rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
#>     unsplit, which.max, which.min
#> Loading required package: S4Vectors
#> 
#> Attaching package: 'S4Vectors'
#> The following object is masked from 'package:utils':
#> 
#>     findMatches
#> The following objects are masked from 'package:base':
#> 
#>     I, expand.grid, unname
#> Loading required package: IRanges
#> Loading required package: GenomeInfoDb
GenoSig <- GRanges("chr1", IRanges(seq(1, 100, by = 10), width = 10),
  score = seq.int(10)
)
pos <- matrix(rnorm(303), ncol = 3)
pos <- cbind(
  x0 = pos[seq.int(100), 1],
  x1 = pos[seq.int(101)[-1], 1],
  y0 = pos[seq.int(100), 2],
  y1 = pos[seq.int(101)[-1], 2],
  z0 = pos[seq.int(100), 3],
  z1 = pos[seq.int(101)[-1], 3]
)
targetObj <- GRanges("chr1", IRanges(seq.int(100), width = 1))
mcols(targetObj) <- pos
ds <- create3dGenomicSignals(GenoSig, targetObj,
  signalTransformFun = function(x) {
    log2(x + 1)
  },
  reverseGenomicSigs = FALSE,
  type = "segment",
  lwd.maxGenomicSigs = 8,
  name = "test",
  tag = "test"
)
threeJsViewer(ds)