An empirical model is fitted into the observed EEJ signatures separately for both the hemispheres, to obtain the parameters of electrojet current such as peak current density, total eastward current, the width of EEJ, position of the electrojet axis, etc.
A cumulative positive and negative score is obtained by aggregating the scores for the positively and negatively associated signatures separately.
Gene signatures separately identified from these data sets by our strategy were used as features to predict the reoperative treatment response of breast cancer, the overall survival milestone outcome of acute myeloma leukemia, and the molecular subclasses of high-grade glioblastoma.
We next performed univariate and multivariate Cox analyses, which included the traditional clinico-pathological parameters, for each signature separately.
In addition, multivariate Cox proportional hazard models were fitted with lymph node (LN) status, size, estrogen receptor (ER) status (DMFS only) and each signature separately (see Additional data file 1, Table S2).
Examination of our novel gene signature separately among patients with either ER+ or ER- breast carcinomas revealed that although the predictive accuracy was diminished relative to the entire cohort, no differences in either accuracy or fitted model coefficients existed between the two subsets.
Of note, the signatures obtained separately for the PTPN11, SOS1, and SHOC2 mutations were found to discriminate more efficiently the individual mutation groups from controls, compared to the signature characterizing the entire "RASopathy" cohort of PBMCs with mutated PTPN11, SOS1, and SHOC2 alleles, indicating occurrence of significant heterogeneity among subgroups.
To investigate this, we performed an ANOVA analysis on the log10 ratios for each of the 70 signature genes separately, to see if they varied significantly between hybridization or labeling sites.
Predictive accuracy of the gene expression signature was evaluated separately within either ER+ or ER- subsets of carcinomas to determine whether efficacy of the signature was maintained for these groups of patients.
To evaluate whether efficacy of the gene expression signature was maintained separately within either ER+ or ER- subsets, C-index values were calculated for each test set stratified by ER+ or ER- status.
Let n be the number of neighbours shared by two signature hubs detected separately from two datasets, and k is the number of these shared neighbours whose correlation changes with these two hubs are in the same direction across the two datasets.
