@author: jyeung
Interaction network is too large for diffusion network (inverse of matrix), we will try
to filter genes to only ones that are outliers or differentially spliced.
'''
import sys
import os
import csv
from utilities import set_directories, read_write_data
# Set constants
input_folder = 'input'
output_folder = 'output'
mydirs = set_directories.paths(input_folder, output_folder)
# Gene name column name
genename_colname = 'Name'
def extract_gene_names_from_textfile(file_fullpath, genename_colname):
'''
Reads a file and tries to find the gene name and returns a list of all
the gene names in that file. File name requires a header with
column name that specifies which column the gene name is located.
Inputs:
file_fullpath: a textfile containing a list of genes in one column.
genename_colname: column name containing column of genes.
Outputs:
gene_list: list of genes in textfile.
'''
'''
Created on 2013-05-23
@author: jyeung
'''
import os
import sys
from utilities import set_directories, influence, correlations, plot_correlations
# Set directories
path = set_directories.paths('input', 'output')
# Set constants
hprdfolder = 'hprd'
textoutputfolder = 'text_outputs'
# influence_filename1 = 'hprd_full_table3.txt'
# influence_filename2 = 'HPRD_InfluenceGraph_HotNet.txt'
if __name__ == '__main__':
if len(sys.argv) < 3:
print('Two influence matrices must be provided in command line.')
sys.exit()
# Define filenames
influence_filename1 = sys.argv[1]
influence_filename2 = sys.argv[2]
# Define full path names
influence_fpath1 = os.path.join(path.outputdir, hprdfolder,
textoutputfolder, influence_filename1)
'''
Created on 2013-05-23
@author: jyeung
'''
import os
import sys
from utilities import set_directories, influence, correlations, plot_correlations
# Set directories
path = set_directories.paths('input', 'output')
# Set constants
hprdfolder = 'hprd'
textoutputfolder = 'text_outputs'
# influence_filename1 = 'hprd_full_table3.txt'
# influence_filename2 = 'HPRD_InfluenceGraph_HotNet.txt'
if __name__ == '__main__':
if len(sys.argv) < 3:
print('Two influence matrices must be provided in command line.')
sys.exit()
# Define filenames
influence_filename1 = sys.argv[1]
influence_filename2 = sys.argv[2]
Created on 2013-06-08
@author: jyeung
Interaction network is too large for diffusion network (inverse of matrix), we will try
to filter genes to only ones that are outliers or differentially spliced.
'''
import sys
import os
import csv
from utilities import set_directories, read_write_data
# Set constants
input_folder = 'input'
output_folder = 'output'
mydirs = set_directories.paths(input_folder, output_folder)
# Gene name column name
genename_colname = 'Name'
def extract_gene_names_from_textfile(file_fullpath, genename_colname):
'''
Reads a file and tries to find the gene name and returns a list of all
the gene names in that file. File name requires a header with
column name that specifies which column the gene name is located.
Inputs:
file_fullpath: a textfile containing a list of genes in one column.
genename_colname: column name containing column of genes.
Outputs:
gene_list: list of genes in textfile.