import os
import gzip
import shutil
import pandas as pd
from scipy import io
def write_to_files(sparse_matrix, top_cells, ordered_tags_map, data_type, outfolder):
"""Write the umi and read sparse matrices to file in gzipped mtx format.
Args:
sparse_matrix (dok_matrix): Results in a sparse matrix.
top_cells (set): Set of cells that are selected for output.
ordered_tags_map (dict): Tags in order with indexes as values.
data_type (string): A string definning if the data is umi or read based.
outfolder (string): Path to the output folder.
"""
prefix = os.path.join(outfolder,data_type + '_count')
os.makedirs(prefix, exist_ok=True)
io.mmwrite(os.path.join(prefix,'matrix.mtx'),sparse_matrix)
with gzip.open(os.path.join(prefix,'barcodes.tsv.gz'), 'wb') as barcode_file:
for barcode in top_cells:
barcode_file.write('{}\n'.format(barcode).encode())
with gzip.open(os.path.join(prefix,'features.tsv.gz'), 'wb') as feature_file:
for feature in ordered_tags_map:
feature_file.write('{}\n'.format(feature).encode())
with open(os.path.join(prefix,'matrix.mtx'),'rb') as mtx_in:
with gzip.open(os.path.join(prefix,'matrix.mtx') + '.gz','wb') as mtx_gz:
shutil.copyfileobj(mtx_in, mtx_gz)
os.remove(os.path.join(prefix,'matrix.mtx'))
def write_dense(sparse_matrix, index, columns, outfolder, filename):
"""
Writes a dense matrix in a csv format
Args:
sparse_matrix (dok_matrix): Results in a sparse matrix.
index (list): List of TAGS
columns (set): List of cells
outfolder (str): Output folder
filename (str): Filename
"""
prefix = os.path.join(outfolder)
os.makedirs(prefix, exist_ok=True)
pandas_dense = pd.DataFrame(sparse_matrix.todense(), columns=columns, index=index)
pandas_dense.to_csv(os.path.join(outfolder,filename), sep='\t')
def write_unmapped(merged_no_match, top_unknowns, outfolder, filename):
"""
Writes a list of top unmapped sequences
Args:
merged_no_match (Counter): Counter of unmapped sequences
top_unknowns (int): Number of unmapped sequences to output
outfolder (string): Path of the output folder
filename (string): Name of the output file
"""
top_unmapped = merged_no_match.most_common(top_unknowns)
with open(os.path.join(outfolder, filename),'w') as unknown_file:
unknown_file.write('tag,count\n')
for element in top_unmapped:
unknown_file.write('{},{}\n'.format(element[0],element[1]))
