FFY.py

#!/usr/bin/env python

# lib

import argparse
import json
import warnings

import numpy as np
import sys

# params

betas = [
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]

intercept = -0.01736036865

gender_cutoff = 0.02


# calculate
def ffy_and_gender(infile):
    npz = np.load(infile, encoding='latin1', allow_pickle=True)
    read_counts = npz['sample'].item()
    read_depth = float(np.sum([np.sum(read_counts[x]) for x in [str(y) for y in range(1, 25)]]))
    y = np.array(read_counts['24'], dtype='float') / read_depth

    ffy = (intercept + np.sum(np.multiply(betas, y)))

    if ffy > gender_cutoff:
        gender = 'male'
    else:
        gender = 'female'

    return {'FFY': ffy, 'gender': gender}


def main():
    warnings.filterwarnings('ignore')
    parser = argparse.ArgumentParser(description='FFY')
    parser.add_argument('infile', help='.npz input file')
    parser.add_argument('--json', action='store_true', help='output as json')

    parser.set_defaults(func=ffy_and_gender)
    args = parser.parse_args(sys.argv[1:])

    result = args.func(args.infile)

    if args.json:
        print(json.dumps(result))
    else:
        print('FFY = {}%'.format(np.round(result['FFY'] * 100, 4)))
        print('Gender = {}'.format(result['gender']))


if __name__ == '__main__':
    main()