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Align the repeat arrays of a tales object

Source: R/tales_msa_class.R
tales_align.Rd

Aligns TALE arrays on one of their residue layers with MAFFT's text mode, returning the alignment as a tales_msa — the input object with an alignment_position column added, so every other layer (rvd, dom_code, aa_seq, ...) remains available.

Usage

tales_align(
  x,
  residue_col = c("rvd", "dom_code"),
  domain_distances = NULL,
  mafft_opts = "--localpair --maxiterate 1000 --reorder --op 0 --ep 5 --thread 1",
  mafft_path = NULL,
  mafft_verbose = FALSE
)

Arguments

x

A tales object holding complete arrays.

residue_col

Which layer to align on: "rvd" (default) or "dom_code".

domain_distances

Scoring matrix for the residues being aligned. NULL (default) means none. Pass "rvd" to opt in to the built-in RVD similarity matrix when aligning RVDs, or, when aligning domain codes, a domain_distances-class object (as returned by tales_domain_distances) or the path to a *_Repeatmatrix.mat file written by Distal.

mafft_opts

Command-line options handed to MAFFT. The default, "--localpair --maxiterate 1000 --reorder --op 0 --ep 5 --thread 1", asks for an accurate local alignment and sets the gap penalties.

--op is the cost of opening a gap and --ep the cost of extending one. They are set unusually here – free to open, expensive to extend – because of what is being aligned. A TALE gains or loses whole repeats, so a gap should start wherever it needs to; what should be discouraged is one long gap swallowing a stretch of repeats that really do correspond. Raise --op if the alignment fragments into too many small gaps.

mafft_path

Where to find MAFFT. NULL, the default, uses the tantale conda environment, created on first use. Give the root of a standalone MAFFT directory instead (one holding mafft.bat with the helpers under mafftdir/libexec) to use your own copy – but note that the version matters: MAFFT changed how it aligns text-mode sequences after 7.4x, and later releases leave the termini of a TALE alignment unanchored.

mafft_verbose

Whether to let MAFFT write to the console. It reports its banner, the strategy it chose and its progress through the sequences, which is dozens of lines per alignment and rarely what you want. With FALSE, that output is captured and replayed if the alignment fails, so nothing is lost for diagnosis.

Value

A tales_msa object. The settings it was aligned with (residue_col, domain_distances, mafft_opts) are kept with it; tales_msa_params returns them.

Details

The mapping back from MAFFT's output is positional: the k-th non-gap cell of an aligned row is the k-th part fed in. That is well defined only because this function builds MAFFT's input from x itself, which is why tales_assert_complete is enforced first.

See also

Other TALE alignment: as.matrix.tales_msa(), is_tales_msa(), tales_consensus(), tales_consensus_match(), tales_msa(), tales_msa_params(), tales_msa_width(), validate_tales_msa()

Examples

# \donttest{
# Needs MAFFT, resolved from the tantale conda environment on first use.
rvd_fasta <- system.file("extdata", "TalA_RVDSeqs_AnnoTALE.fasta",
                         package = "tantale")
x <- as_tales(rvd_fasta, sep = "-")
msa <- tales_align(x, residue_col = "rvd")
#> Now running MAFFT (Copyright 2002-2007 Kazutaka Katoh) on TALE array sequences.
as.matrix(msa)
#>               1    2    3    4    5    6    7    8    9    10   11   12   13  
#> TalA_BAI3     "NN" "NG" "NN" "HD" "HD" "NI" "N*" "NG" "HD" "NI" "NG" "NN" "HD"
#> TalA_CFBP1947 "NN" "NG" "NN" "HD" "HD" "NI" "N*" "NG" "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI1     "NN" "N*" "NN" "HD" "HD" "NI" "N*" "NG" "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI106   "NN" "N*" "NN" "HD" NA   NA   NA   NA   "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI129   "NN" "N*" "NN" "HD" NA   NA   NA   NA   "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI134   "NN" "N*" "NN" "HD" "HD" "NI" "N*" "NG" "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI145   "NN" "N*" "NN" "HD" NA   NA   NA   NA   "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI68    "NN" "N*" "NN" "HD" NA   NA   NA   NA   "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI73    "NN" "N*" "NN" "HD" NA   NA   NA   NA   "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI95    "NN" "N*" "NN" "HD" NA   NA   NA   NA   "HD" "NI" "NG" "NN" "HD"
#> TalA_MAI99    "NN" "N*" "NN" "HD" NA   NA   NA   NA   "HD" "NI" "NG" "NN" "HD"
#>               14   15   16   17   18   19   20   21   22   23   24   25   26  
#> TalA_BAI3     "NI" "NG" "NI" "NG" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_CFBP1947 "NI" "NG" "NI" "NG" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI1     "NS" "NG" "NI" "NG" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI106   "NS" "NG" "NI" "N*" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI129   "NS" "NG" "NI" "N*" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI134   "NS" "NG" "NI" "NG" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI145   "NS" "NG" "NI" "N*" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI68    "NS" "NG" "NI" "N*" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI73    "NS" "NG" "NI" "N*" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI95    "NS" "NG" "NI" "N*" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
#> TalA_MAI99    "NS" "NG" "NI" "N*" "NN" "NG" "HD" "NI" "NI" "NG" "HD" "NN" "NG"
# }