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# -*- coding: utf-8 -*-
# (c) The James Hutton Institute 2016-2019
# (c) University of Strathclyde 2019-2020
# Author: Leighton Pritchard
#
# Contact: leighton.pritchard@strath.ac.uk
#
# Leighton Pritchard,
# Strathclyde Institute for Pharmacy and Biomedical Sciences,
# Cathedral Street,
# Glasgow,
# G4 0RE
# Scotland,
# UK
#
# The MIT License
#
# Copyright (c) 2016-2019 The James Hutton Institute
# Copyright (c) 2019-2020 University of Strathclyde
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
"""Code to support pyani with miscellaneous functions."""
import pandas as pd
from . import pyani_config
# Class to hold ANI dataframe results
class ANIResults(object):
"""Holds ANI dataframe results."""
def __init__(self, labels, mode):
"""Initialise with four empty, labelled dataframes."""
self.alignment_lengths = pd.DataFrame(index=labels, columns=labels, dtype=float)
self.similarity_errors = pd.DataFrame(
index=labels, columns=labels, dtype=float
).fillna(0)
self.percentage_identity = pd.DataFrame(
index=labels, columns=labels, dtype=float
).fillna(1.0)
self.alignment_coverage = pd.DataFrame(
index=labels, columns=labels, dtype=float
).fillna(1.0)
self.zero_error = False
self.mode = mode
def add_tot_length(self, qname, sname, value, sym=True):
"""Add a total length value to self.alignment_lengths."""
self.alignment_lengths.loc[qname, sname] = value
if sym:
self.alignment_lengths.loc[sname, qname] = value
def add_sim_errors(self, qname, sname, value, sym=True):
"""Add a similarity error value to self.similarity_errors."""
self.similarity_errors.loc[qname, sname] = value
if sym:
self.similarity_errors.loc[sname, qname] = value
def add_pid(self, qname, sname, value, sym=True):
"""Add a percentage identity value to self.percentage_identity."""
self.percentage_identity.loc[qname, sname] = value
if sym:
self.percentage_identity.loc[sname, qname] = value
def add_coverage(self, qname, sname, qcover, scover=None):
"""Add percentage coverage values to self.alignment_coverage."""
self.alignment_coverage.loc[qname, sname] = qcover
if scover:
self.alignment_coverage.loc[sname, qname] = scover
@property
def hadamard(self):
"""Return Hadamard matrix (identity * coverage)."""
return self.percentage_identity * self.alignment_coverage
@property
def data(self):
"""Return list of (dataframe, filestem) tuples."""
stemdict = {
"ANIm": pyani_config.ANIM_FILESTEMS,
"ANIb": pyani_config.ANIB_FILESTEMS,
"ANIblastall": pyani_config.ANIBLASTALL_FILESTEMS,
}
return zip(
(
self.alignment_lengths,
self.percentage_identity,
self.alignment_coverage,
self.similarity_errors,
self.hadamard,
),
stemdict[self.mode],
)
# return [(self.alignment_lengths, "ANIm_alignment_lengths"),
# (self.percentage_identity, "ANIm_percentage_identity"),
# (self.alignment_coverage, "ANIm_alignment_coverage"),
# (self.similarity_errors, "ANIm_similarity_errors"),
# (self.hadamard, "ANIm_hadamard")]
# Class to hold BLAST functions
class BLASTfunctions(object):
"""Class to hold BLAST functions."""
def __init__(self, db_func, blastn_func):
"""Initialise struct to hold BLAST functions."""
self.db_func = db_func
self.blastn_func = blastn_func
# Class to hold BLAST executables
class BLASTexes(object):
"""Class to hold BLAST functions."""
def __init__(self, format_exe, blast_exe):
"""Initialise struct to hold BLAST functions."""
self.format_exe = format_exe
self.blast_exe = blast_exe
# Class to hold/build BLAST commands
class BLASTcmds(object):
"""Holds BLAST command/database formatting commands."""
def __init__(self, funcs, exes, prefix, outdir):
"""Initialise BLASTcmds."""
self.funcs = funcs
self.exes = exes
self.prefix = prefix
self.outdir = outdir
def build_db_cmd(self, fname):
"""Return database format/build command."""
return self.funcs.db_func(fname, self.outdir, self.exes.format_exe)[0]
def get_db_name(self, fname):
"""Return database filename."""
return self.funcs.db_func(fname, self.outdir, self.exes.format_exe)[1]
def build_blast_cmd(self, fname, dbname):
"""Return BLASTN command."""
return self.funcs.blastn_func(fname, dbname, self.outdir, self.exes.blast_exe)
# Read sequence annotations in from file
def get_labels(filename, logger=None):
r"""Return dictionary of alternative sequence labels, or None.
- filename - path to file containing tab-separated table of labels
Input files should be formatted as <key>\t<label>, one pair per line.
"""
labeldict = {}
if filename is not None:
if logger:
logger.info("Reading labels from %s", filename)
with open(filename, "r") as ifh:
count = 0
for line in ifh.readlines():
count += 1
try:
key, label = line.strip().split("\t")
except ValueError:
if logger:
logger.warning("Problem with class file: %s", filename)
logger.warning("%d: %s", (count, line.strip()))
logger.warning("(skipping line)")
continue
else:
labeldict[str(key)] = str(label)
return labeldict
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