itaxotools-pygblocks

Python implementation for Gblocks


Licenses
GPL-3.0/GPL-3.0+
Install
pip install itaxotools-pygblocks==0.1.0

Documentation

PyGblocks

PyPI - Version PyPI - Python Version GitHub - Tests

Pure Python implementation for the algorithm behind Gblocks.

Differences

  • Can define which characters are considered as gaps
  • Any character that is not defined as a gap is considered for conservation
  • Can define how many gaps are allowed per position (number or percentage)
  • Positions that only contain gaps are not pre-emptively removed
  • Conservation threshold may be set below 50%
  • No support for similarity matrices

Installation

PyGblocks is available on PyPI. You can install it through pip:

pip install itaxotools-pygblocks

Usage

First create a mask from your sequences, then apply that mask to each sequence:

from itaxotools.pygblocks import compute_mask, trim_sequences

sequences = [
    "--TTTNNTACTTTTTTT-ATT",
    "--TTTNTTACGTTTTTG-ATT",
    "--TTTNTTAGTTTTTTC-ATT",
]

mask = compute_mask(sequences)
trimmed_sequences = trim_sequences(sequences, mask)

You may customize the trimming parameters and enable logging when creating the mask:

from itaxotools.pygblocks import Options, compute_mask

options = Options(
    IS=2,    # Minimum Number Of Sequences For A Conserved Position
    FS=3,    # Minimum Number Of Sequences For A Flank Position
    CP=2,    # Maximum Number Of Contiguous Nonconserved Positions
    BL1=3,   # Minimum Length Of A Block, 1st iteration
    BL2=3,   # Minimum Length Of A Block, 2nd iteration
    GT=2,    # Maximum Number of Allowed Gaps For Any Position
    GC="-",  # Definition of Gap Characters
)

mask = compute_mask(sequences, options, log=True)

You may optionally set IS, FS and GT as a percentage of the number of sequences by setting IS, FS and GT values to zero, then modifying the percentage defaults if desired:

options = Options(
    IS=0, FS=0, CP=2, BL1=3, BL2=3, GT=0, GC="-",

    IS_percent = 0.50
    FS_percent = 0.85
    GT_percent = 0.00
)

mask = compute_mask(sequences, options, log=True)

You may find the above examples, plus some examples on how to use PyGblocks with BioPython alignments, in the scripts folder.

Citations

Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000 Apr;17(4):540-52. doi: 10.1093/oxfordjournals.molbev.a026334. PMID: 10742046.