def preparedata(cancer,gene5p,gene3p,folder=None):
if not folder:
folder = os.getcwd()
gct_file = os.path.join(folder,cancer + '.gct')
if not os.path.isfile(gct_file):
writeTCGAExpressionMatrix([cancer], folder=folder)
col_file = os.path.join(folder,'_'.join([cancer,gene5p,gene3p,'colData']))
prepareColdata(gct_file,col_file,fusion=(gene5p,gene3p),cancer=cancer,
map_path='/home/staff/hes14/Roche/Data/connect/ccle_tcga_mapping_v1.txt')
"""
Pipeline work (Python part) for differential expression analysis
Created on Jul 28, 2014
@author: HSH
"""
import sys
sys.path.append("/Users/HSH/Roche/workspace/GeneFusion/DESeq")
from getExpressionData import writeTCGAExpressionMatrix
from prepareDESeqData import prepareColdata
cancer = "BLCA"
gene = "TACC3"
partner = "FGFR3"
date = "20140908"
gct_file = "/Users/HSH/Roche/Data/expression/" + cancer + ".gct"
col_file = "/Users/HSH/Roche/" + date + "/" + "_".join([cancer, gene, "colData"])
writeTCGAExpressionMatrix([cancer], folder="/Users/HSH/Roche/Data/expression/")
result = prepareColdata(
gct_file,
col_file,
fusion=(partner, gene),
cancer=cancer,
map_path="/Users/HSH/Roche/Data/connect/ccle_tcga_mapping_v1.txt",
)
