File size: 3,178 Bytes
e3814d7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | # This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# --------------------------------------------------------
# a script to help convert .npz files to .cool files.
# --------------------------------------------------------
import argparse
import os
import numpy as np
from dataset_informations import *
from tqdm import tqdm
from data_processing.Read_npz import read_npz
from data_processing.Read_external_norm import read_singlechromosome_norm
import cooler
import pandas as pd
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--data-dir', type=str, required = True)
parser.add_argument('--hic-caption', type=str, default = 'hic')
parser.add_argument('--external-norm-file', type=str,
default = f'{root_dir}/{RAW_dir}/#(CELLLINE)/10kb_resolution_intrachromosomal/#(CHR)/MAPQGE30/#(CHR)_10kb.KRnorm')
parser.add_argument('--resolution', type=str, default='10kb')
parser.add_argument('--bound', type=int, default=200)
parser.add_argument('--multiple', type=int, default=255)
parser.add_argument('-c', '--cell-line', default='GM12878')
parser.add_argument('-s', '--dataset', default='test', choices=['train', 'valid', 'test', 'train1', 'valid1', 'test1'], )
args = parser.parse_args()
data_dir = args.data_dir
hic_caption = args.hic_caption
external_norm_file = args.external_norm_file
res = args.resolution
cell_line = args.cell_line
dataset = args.dataset
bound = args.bound
multiple = args.multiple
resolution = res_map[res.split('_')[0]]
chr_list = set_dict[dataset]
abandon_chromosome = abandon_chromosome_dict.get(cell_line, [])
bins = {"chrom": [], "start": [], "end": []}
reads = {"bin1_id": [], "bin2_id": [], "count": []}
for n in tqdm(chr_list):
if n in abandon_chromosome:
continue
in_file = os.path.join(data_dir, f'chr{n}_{res}.npz')
matrix, compact_idx, norm = read_npz(in_file, hic_caption = hic_caption, bound = bound, multiple=multiple, include_additional_channels=False)
if external_norm_file != 'NONE':
if '#(CHR)' in external_norm_file:
norm = read_singlechromosome_norm(external_norm_file, n, cell_line)
else:
raise NotImplementedError
s = len(bins['chrom'])
for i in range(matrix.shape[0]):
bins['chrom'].append(f'chr{n}')
bins['start'].append(i*resolution)
bins['end'].append((i+1)*resolution)
for i in tqdm(range(matrix.shape[0]), leave=False):
for j in range(i, min(i+bound, matrix.shape[1])):
RAW = float(matrix[i][j])*norm[i]*norm[j]
if RAW > 0:
reads['bin1_id'].append(s+i)
reads["bin2_id"].append(s+j)
reads["count"].append(matrix[i][j])
cool_file = os.path.join(data_dir, f"bound{bound}_{res}.cool")
cooler.create_cooler(cool_file, bins=pd.DataFrame.from_dict(bins), pixels=pd.DataFrame.from_dict(reads), dtypes={'count': float})
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