gseapy/gsea.py
def norm_samples(self, dat):
        """normalization samples
           see here: http://rowley.mit.edu/caw_web/ssGSEAProjection/ssGSEAProjection.Library.R
        """

        if self.sample_norm_method == 'rank':
            data = dat.rank(axis=0, method='average', na_option='bottom')
            data = 10000*data / data.shape[0]
        elif self.sample_norm_method == 'log_rank':
            data = dat.rank(axis=0, method='average', na_option='bottom')
            data = log(10000*data / data.shape[0] + exp(1))
        elif self.sample_norm_method == 'log':
            dat[dat < 1] = 1
            data = log(dat + exp(1))
        elif self.sample_norm_method == 'custom':
            self._logger.info("Use custom rank metric for ssGSEA")
            data = dat
        else:
            sys.stderr.write("No supported method: %s"%self.sample_norm_method)
            sys.exit(0)

        return data
def norm_samples(self, dat):
        """normalization samples
           see here: http://rowley.mit.edu/caw_web/ssGSEAProjection/ssGSEAProjection.Library.R
        """

        if self.sample_norm_method == 'rank':
            data = dat.rank(axis=0, method='average', na_option='bottom')
            data = 10000*data / data.shape[0]
        elif self.sample_norm_method == 'log_rank':
            data = dat.rank(axis=0, method='average', na_option='bottom')
            data = log(10000*data / data.shape[0] + exp(1))
        elif self.sample_norm_method == 'log':
            dat[dat < 1] = 1
            data = log(dat + exp(1))
        elif self.sample_norm_method == 'custom':
            self._logger.info("Use custom rank metric for ssGSEA")
            data = dat
        else:
            sys.stderr.write("No supported method: %s"%self.sample_norm_method)
            sys.exit(0)

        return data
def norm_samples ( self , dat ) : if self . sample_norm_method == 'rank' : data = dat . rank ( axis = 0 , method = 'average' , na_option = 'bottom' ) data = 10000 * data / data . shape [ 0 ] elif self . sample_norm_method == 'log_rank' : data = dat . rank ( axis = 0 , method = 'average' , na_option = 'bottom' ) data = log ( 10000 * data / data . shape [ 0 ] + exp ( 1 ) ) elif self . sample_norm_method == 'log' : dat [ dat < 1 ] = 1 data = log ( dat + exp ( 1 ) ) elif self . sample_norm_method == 'custom' : self . _logger . info ( "Use custom rank metric for ssGSEA" ) data = dat else : sys . stderr . write ( "No supported method: %s" % self . sample_norm_method ) sys . exit ( 0 ) return data
normalization samples
           see here: http://rowley.mit.edu/caw_web/ssGSEAProjection/ssGSEAProjection.Library.R
normalization samples see here : http : // rowley . mit . edu / caw_web / ssGSEAProjection / ssGSEAProjection . Library . R