def getRedirectURL(choices):
     
     genome = choices[0]
     track1file = ExternalTrackManager.createSelectValueFromGalaxyTN(choices[1].split(':'))
     track2file = ExternalTrackManager.createSelectValueFromGalaxyTN(choices[2].split(':'))
     return createHyperBrowserURL(genome, trackName1=['galaxy'], trackName2=['galaxy'], \
                                  track1file=track1file, track2file=track2file, \
                                  analysis='Category pairs differentially co-located?', \
                                  configDict={'Method of counting points': 'Only 1 count per bin (binary)',\
                                              'Normalize counts': 'Differentially in both directions' if \
                                              choices[3] == 'Both rows and columns (focusing on column differences)'\
                                              else 'Differentially for points only',\
                                              'P-value threshold for significance': '0.01'},\
                                  method='__chrs__')
Пример #2
0
    def getRedirectURL(choices):

        genome = choices[0]
        track1file = ExternalTrackManager.createSelectValueFromGalaxyTN(
            choices[1])
        track2file = ExternalTrackManager.createSelectValueFromGalaxyTN(
            choices[2])
        return createHyperBrowserURL(genome, trackName1=['galaxy'], trackName2=['galaxy'], \
                                     track1file=track1file, track2file=track2file, \
                                     analysis='Category pairs differentially co-located?', \
                                     configDict={'Method of counting points': 'Only 1 count per bin (binary)',\
                                                 'Normalize counts': 'Differentially in both directions' if \
                                                 choices[3] == 'Both rows and columns (focusing on column differences)'\
                                                 else 'Differentially for points only',\
                                                 'P-value threshold for significance': '0.01'},\
                                     method='__chrs__')