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Last data update: 2014.03.03

R: Assign colours to helices

Colour Helices

R Documentation

Assign colours to helices

Description

Functions to generate colours for helices by various rules, including integer counts, value ranges, percent identity covariation, conservation, percentage canonical basepair, basepair frequency, and non-pseudoknotted groups.

Usage

    colourByCount(helix, cols, counts, get = FALSE)
    colourByValue(helix, cols, breaks, get = FALSE,
        log = FALSE, include.lowest = TRUE, ...)
    colourByBasepairFrequency(helix, cols, get = TRUE)
    colourByUnknottedGroups(helix, cols, get = TRUE)
    colourByCovariation(helix, msa, cols, get = FALSE)
    colourByConservation(helix, msa, cols, get = FALSE)
    colourByCanonical(helix, msa, cols, get = FALSE)
    defaultPalette()

Arguments

`helix`	A helix data frame to be coloured.
`cols`	An array of characters (or numbers) representing a set of colours to colour `helix` with. When missing, a default set of colours from defaultPalette() will be used. Valid input include hex codes, colour names from the `colours` function, and integer numbers. The colours will be interpreted as being from best to worst.
`counts`	An array of integers the same length as `cols`, dictating the number of times each corresponding colour should be used. When missing, the function will divide the number of helices evenly over each of the colours available.
`breaks`	An integer number of intervals to break the ‘value’ column of `helix` into, or a list of numbers defining the interval breaks. If missing, the range of ‘helix$value’ will automatically be split evenly into intervals for each colour available.
`get`	If TRUE, returns the input `helix` with a `col` column, else simply returns an array of colours the same length as the number of row in `helix`. The exceptions are `colourByBasepairFrequency` and `colourByUnknottedGroups` which will return a different helix if TRUE, and a list of colours that will not match the input helix if FALSE.
`log`	If TRUE, will breaks values into even log10 space intervals, useful when values are p-values.
`include.lowest`	Whether the lowest interval should include the lowest value, passed to `cut`
`...`	Additional arguments passed to `cut`, potentially useful ones include `right` (whether intervals should be inclusive on the right or left) and `dig.lab` (number of digits in interval labels).
`msa`	A multiple sequence alignment. Can be either a `Biostrings` `XStringSet` object or a named array of strings like ones obtained from converting XStringSet with `as.character`.

Details

colourByCount assigns colours indepenent of the helix input's value column, and instead operates over the number of helices (i.e. rows).

colourByValue uses cut to assign each of the helices to an interval based on its value.

colourByCovariation, colourByConservation , and colourByCanonical, colour helices according to compensatory mutations (or covariation), percentage identity conservation, and percentage canonical basepair repsectively, relative to the multiple sequence alignment provided.

colourByBasepairFrequency colours each basepair according to the number of times it appear in the input, regardless of its value.

colourByUnknottedGroups greedily partitions the basepairs into non- pseudoknotted groups, and assigns a colour to each.

Value

All “colourBy” functions return a list of colours when get = FALSE, and a helix with a col column if get = TRUE. In both bases, the returned object has attributes “legend” and “fill”, showing the mapping between interval (in legend) and colour (in fill), which can as eponymous arguments legend.

defaultPalette returns the default list of colours.

Author(s)

Daniel Lai

Examples

    data(helix)

    known$col <- colourByCount(known)
    plotHelix(known)

    plotHelix(colourByValue(helix, log = TRUE, get = TRUE))

    cov <- colourByCovariation(known, fasta, get = TRUE)
    plotCovariance(fasta, cov)
    legend("topleft", legend = attr(cov, "legend"),
        fill = attr(cov, "fill"), title = "Covariation")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(R4RNA)
Loading required package: Biostrings
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: XVector
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/R4RNA/colourHelices.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Colour Helices
> ### Title: Assign colours to helices
> ### Aliases: colourByCount colourByValue colourByConservation
> ###   colourByCovariation colourByCanonical colourByBasepairFrequency
> ###   colourByUnknottedGroups defaultPalette
> ### Keywords: color
> 
> ### ** Examples
> 
>     data(helix)
> 
>     known$col <- colourByCount(known)
>     plotHelix(known)
> 
>     plotHelix(colourByValue(helix, log = TRUE, get = TRUE))
> 
>     cov <- colourByCovariation(known, fasta, get = TRUE)
>     plotCovariance(fasta, cov)
>     legend("topleft", legend = attr(cov, "legend"),
+         fill = attr(cov, "fill"), title = "Covariation")
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>