plotAlongChrom {tilingArray} | R Documentation

## Plot signals and segmentation along a chromosomal region

### Description

Plot signals and segmentation along a chromosomal region

### Usage

    plotAlongChrom(segObj, y, probeAnno, gff,
        isDirectHybe=FALSE,
        what = c("dots"), ## "heatmap"
        chr, coord, highlight, ylim,
        colors,
        doLegend=TRUE,
        featureColorScheme=1,
        featureExclude=c("chromosome","gene","nucleotide_match", "insertion", "intron"),
        featureNoLabel=c("uORF"),
        pointSize=unit(0.6, "mm"),
        main, ...)

### Arguments

`segObj` | Either an environment or an object of S4 class `segmentation`. See Details.
`y` | a numeric vector or matrix containing the signal to be plotted. See Details.
`probeAnno` | environment with probe annotations. See Details, and package `davidTiling` for an example.
`gff` | data frame with genome annotation from the GFF file.
`isDirectHybe` | logical scalar: if TRUE, the mapping of probes to genomic strands is reversed with respect to the default. This is appropriate for data from a direct RNA hybridization that used no reverse transcription.
`what` | character scalar, choice of signal visualization, can be either `dots` or `heatmap`
`chr` | integer of length 1 with the number of the chromosome for which to produce the plot.
`coord` | integer of length 2 with start and end coordinates (in bases) for which to produce the plot.
`highlight` | optional, list with two elements: a single numeric value `coord` and a character `strand`. If present, this position is marked by a vertical red bar on the coordinate axis.
`ylim` | numeric vector of length two with y-axis limits.
`colors` | named character vector, optional. If missing, a default color scheme is used: `c("+"="#00441b", "-"="#081d58", "duplicated"="grey", "cp"="#101010", "highlight"="red", "threshold"="grey")`, where the first three elements refer to colors of data points and the last three to those of lines in the plot.
`doLegend` | logical: should the plot contain a legend?
`featureColorScheme` | numeric scalar, used to select a color scheme for the boxes representing genomic features such as coding sequences, ncRNAs etc. Currently the values 1 and 2 are supported.
`featureExclude` | character vector, names of feature types (in gff) that should not be plotted. Additional possible candidates include: "ARS", "repeat_region", "repeat_family", "nc_primary_transcript".
`featureNoLabel` | character vector, names of feature types (in gff) that should not be labeled with their names (if they are plotted).
`pointSize` | unit object: point size used for the probe intensities scatterplot.
`main` | character: plot title.
`...` | further arguments that can be passed on to the the functions that implement the `what` option (see above), `plotSegmentationDots` and `plotSegmentationHeatmap`.

### Details

Intensities: There are two alternative, mutually exclusive ways of providing the intensities that are to be plotted to this function.

1. Via the parameters `y` and `probeAnno`. In this case, `y` is a matrix of intensities, whose rows correspond to probes on the array, and its columns to different conditions, time points, etc. It is also acceptable that `y` is provided as a vector, in which case it is converted to an `nrow(y) x 1` matrix. `probeAnno` is an environment whose elements correspond to target sequences (e.g. chromosome strands) and that contain integer vectors of length `nrow(y)` with information about the probes: start and end positions of their alignment to the target sequence, their row indices in `y`, the type of alignment (is it perfect? is is unique?). For example, the start positions and indices of probes for the + strand of chromosome 1 would be described by environment elements `"1.+.start"` and `"1.+.index"`.
2. Via the parameter `segObj`.

segObj: This can be either an object of S4 class `segmentation` or an environment that by convention contains a certain set of objects. Future work on this package will focus on the S4 class `segmentation`. The `environment` option is provided for backward compatibility.

Explanation of the environment: the intended workflow is as follows: Use the script `segment.R` (in the `inst/scripts` directory of this package) to generate segmentations. This can be run in parallel on several processors, separately for each chromosome and strand. The results of this are stored in files of the name `1.+.rda`, `1.-.rda`, `2.+.rda`, and so forth, typically within a dedicated directory. Then use the script `readSegments.R` to collect the `R` objects in these `.rda` files into the environment. It contains three types of data:

- microarray intensities in along-chromosome order.
- the segmentation objects (output of findSegments).
- a dataframe named `segScore` with segment scores; it can be missing iff `nrBasesPerSeg` is present,
- a numeric scalar names `theThreshold`, which is used to draw a horizontal "threshold" line in the plot.

... and the different signal visualization methods (`what` option): If `what=="dots"`, the argument `showConfidenceIntervals` can be a logical scalar to choose whether vertical dashed lines are drawn for the confidence interval. In any case, these are only drawn if they are present in the `segmentation` object in `segObj`.

### Author(s)

Wolfgang Huber <huber@ebi.ac.uk>

### Examples

      ## 1. see viewSegmentation.R script in the inst/scripts directory
      ## 2. (newer): segmentation.Rnw

[Package tilingArray version 1.10.0 Index]