MaskAlignment {DECIPHER} | R Documentation

## Mask Highly Variable Regions of An Alignment

### Description

Automatically masks poorly aligned regions of an alignment based on sequence conservation and gap frequency.

### Usage

    MaskAlignment(myXStringSet,
                  type = "sequences",
                  windowSize = 5,
                  threshold = 1,
                  maxFractionGaps = 0.2,
                  includeTerminalGaps = FALSE,
                  correction = FALSE,
                  showPlot = FALSE)

### Arguments

`myXStringSet` | An `AAStringSet`, `DNAStringSet`, or `RNAStringSet` object of aligned sequences.
`type` | Character string indicating the type of result desired. This should be (an abbreviation of) one of `"sequences"`, `"ranges"`, or `"values"`. (See value section below.)
`windowSize` | Integer value specifying the size of the region to the left and right of the center-point to use in calculating the moving average.
`threshold` | Numeric giving the average entropy in bits below which a region is masked.
`maxFractionGaps` | Numeric specifying the maximum faction of gaps in an alignment column to be masked.
`includeTerminalGaps` | Logical specifying whether or not to include terminal gaps ("." or "-" characters on each end of the sequences) into the calculation of gap fraction.
`correction` | Logical indicating whether to apply a small-sample size correction to columns with few letters (Yu et al., 2015).
`showPlot` | Logical specifying whether or not to show a plot of the positions that were kept or masked.

### Details

Poorly aligned regions of a multiple sequence alignment may lead to incorrect results in downstream analyses. One method to mitigate their effects is to mask columns of the alignment that may be poorly aligned, such as highly-variable regions or regions with many insertions and deletions (gaps).

Highly variable regions are detected by their signature of having a low information content. Here, information content is defined by the relative entropy of a column in the alignment (Yu et al., 2015), which is higher for conserved columns. The relative entropy is based on the background distribution of letter-frequencies in the alignment.

A moving average of `windowSize` nucleotides to the left and right of the center-point is applied to smooth noise in the information content signal along the sequence. Regions dropping below `threshold` bits or more than `maxFractionGaps` are masked.

### Value

If `type` is `"sequences"` then a `MultipleAlignment` object of the input type with masked columns where the input criteria are met. Otherwise, if `type` is `"ranges"` then an `IRanges` object giving the start and end positions of the masked columns. Else (`type` is `"values"`) a `data.frame` containing one row per site in the alignment and three columns of information:

`"entropy"` | The entropy score of each column, in units of bits.
`"gaps"` | For each column, the fraction of gap characters ("-" or ".").
`"mask"` | A logical vector indicating whether or not the column met the criteria for masking.

### Author(s)

Erik Wright eswright@pitt.edu

### References

Yu, Y.-K., et al. (2015). Log-odds sequence logos. Bioinformatics, 31(3), 324-331. http://doi.org/10.1093/bioinformatics/btu634

### See Also

`AlignSeqs`, `IdClusters`

### Examples

    fas <- system.file("extdata", "Streptomyces_ITS_aligned.fas", package="DECIPHER")
    dna <- readDNAStringSet(fas)
    masked_dna <- MaskAlignment(dna, showPlot=TRUE)

    # display only unmasked nucleotides for use in downstream analyses
    not_masked <- as(masked_dna, "DNAStringSet")
    BrowseSeqs(not_masked)

    # display only masked nucleotides that are covered by the mask
    masked <- masked_dna
    colmask(masked, append="replace", invert=TRUE) <- colmask(masked)
    masked <- as(masked, "DNAStringSet")
    BrowseSeqs(masked)

    # display the complete DNA sequence set including the mask
    masks <- lapply(width(colmask(masked_dna)), rep, x="+")
    masks <- unlist(lapply(masks, paste, collapse=""))
    masked_dna <- replaceAt(dna, at=IRanges(colmask(masked_dna)), value=masks)
    BrowseSeqs(masked_dna)

    # get the start and end ranges of masked columns
    ranges <- MaskAlignment(dna, type="ranges")
    ranges
    replaceAt(dna, ranges) # remove the masked columns

    # obtain the entropy scores of each column
    values <- MaskAlignment(dna, type="values")
    head(values)

[Package DECIPHER version 2.12.0 Index]