@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.