Source code for plot_cnv_size_dgv_ro

#!/usr/bin/env python2.7

import pickle
import argparse

import mendelian
import parsers
import cnv_db.db
import cnv_struct

import matplotlib.pyplot as plt
import numpy as np

# This file is part of CNVAnalysisToolkit.
# 
# CNVAnalysisToolkit is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# 
# CNVAnalysisToolkit is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
# 
# You should have received a copy of the GNU General Public License
# along with CNVAnalysisToolkit.  If not, see <http://www.gnu.org/licenses/>.

__author__ = "Marc-Andre Legault (StatGen)"
__copyright__ = "Copyright (C) 2013 StatGen"
__license__ = "GNU General Public License v3 (GPL-3)"

def main(args):
    """Plots the best reciprocal to a variant in DGV as a function of CNV size.

    A possible correlation would indicate a biais in the database towards CNVs
    of a given size.

    """
    with open(args.pickle) as f:
        cnvs = pickle.load(f)

    if type(cnvs) is not list:
        cnvs = parsers.family_to_list(cnvs)

    for cnv in cnvs:
        # Manually get the overlap to DGV
        dgv_cnvs = cnv_db.db.query_dgv_overlap(cnv)
        best_ro = cnv_struct.ro_to_best_in_list(cnv, dgv_cnvs)[0]
        cnv.dgv_ro = best_ro

    # Convert to plottable array.
    dgv_overlap_size = []
    quals = []
    for cnv in cnvs:
        if args.plot_confidence:
            if cnv.confidence:
                quals.append(cnv.confidence)
                dgv_overlap_size.append(np.array([cnv.dgv_ro, cnv.size / 1000.0]))
        else:
            dgv_overlap_size.append(np.array([cnv.dgv_ro, cnv.size / 1000.0]))
        
    dgv_overlap_size = np.array(dgv_overlap_size)
    quals = np.array(quals)
    
    fig = plt.figure()
    if len(quals) > 0:
        plt.scatter(
                        dgv_overlap_size[:, 1], 
                        dgv_overlap_size[:, 0],
                        marker = "o",
                        c = quals,
                        cmap = plt.cm.gist_yarg,
                        edgecolors = "none",
                   )
    else:
        plt.scatter(dgv_overlap_size[:, 1], dgv_overlap_size[:, 0], marker = ".")
    plt.ylabel("Overlap to DGV")
    plt.xlabel("Size (kilobase)")
    if args.save is None:
        plt.show()
    else:
        plt.savefig(args.save)

if __name__ == "__main__":
    PARSER = argparse.ArgumentParser("This script takes a pickle and generates "
                                     "the plot of the overlap to DGV with the "
                                     "CNV sizes for either a full family or "
                                     "the Mendelian CNVs, exlusively.")

    PARSER.add_argument("--pickle",
                        type=str,
                        help=("The pickle containing either a CNV list or a "
                              "dictionary like structure containing the CNVs "
                              "for the whole family."),
                        required=True,
                       )

    PARSER.add_argument("--plot_confidence",
                        action='store_true'
                       )

    PARSER.add_argument("--save",
                        type=str,
                        help="Filename of the output graph file.",
                        default=None
                       )

    main(PARSER.parse_args())