fileNames = ['/Users/biggus/Documents/James/Data/ReClustering/PrelimData_Grant_Feb09/Clus2_kmerSearch.6-8mers.FDR_lessThan0.01.txt',] coRegSeqs = '/Users/biggus/Documents/James/Data/ReClustering/kmedsPear33Clus50x_2/Clus2_247genes.genes.txt' allPromoters = promoterSeqPaths.Aa_2000bpUp_hardMasked MDfileType = 'list' dfltFactor = 0.75 coRegSeqs = map(lambda l: l.strip(), open(coRegSeqs, 'rU').readlines()) motifs = [] for f in fileNames: motifs.append([f.split('/')[-1],loadMotifsFromOutFile(f, MDfileType)]) probSet = ProbeSet(allPromoters) # get and print motif and pVal(s) out = '#outFile\tMotif\tHyperGeoPval (%s)\tfrac (%s)\tBestHG (pval)\tfrac (bestHG_ScoreThresh)\tBestHG (scoreThresh)\tbinoPval (%s)\tbinoPval (bestHG_scoreThresh)' \ % (dfltFactor,dfltFactor,dfltFactor) print out out = out+'\n' for m in motifs: for i in m[1]: bestE = probSet.best_p_value(m[1],coRegSeqs) temp ='%s\t%s\t%.3e\t%.3f\t%.3e\t%.3f\t%.3f\t%.3e\t%.3e' % (m[0], m[1], probSet.Enrichment(m[1],coRegSeqs,factor=dfltFactor),
from gusPyCode.MDAP_proj.MDAP_defs import loadMotifsFromOutFile from TAMO import MotifTools mdOutFiles = ['/Users/biggus/Documents/James/Data/ReClustering/PrelimData_Grant_Feb09/RandSplitFastas/AceResults/Clus2_247gene_0.8_Apr16_14-46-33.ace.1.txt', '/Users/biggus/Documents/James/Data/ReClustering/PrelimData_Grant_Feb09/RandSplitFastas/AceResults/Clus2_247gene_0.8_Apr16_14-46-33.ace.2.txt', '/Users/biggus/Documents/James/Data/ReClustering/PrelimData_Grant_Feb09/RandSplitFastas/AceResults/Clus2_247gene_0.8_Apr16_14-46-33.ace.3.txt'] for mdFile in mdOutFiles: motifs = loadMotifsFromOutFile(mdFile,'list') # ['Meme', 'AlignAce', 'MDscan', 'Weeder','list'] MotifTools.save_motifs(motifs,mdFile+'.tmo') print 'Done.'