| survJamda-package | Survival Prediction by Joint Analysis of Microarray Gene Expression Data |
| aprior | Calculate empirical hyper-prior values |
| Beta.NA | Fit the L/S model in the presence of missing data values |
| bprior | Calculate empirical hyper-prior values of Bayesian model |
| build.design | Initiation to build the design matrix |
| cal.cox.coef | Cox coefficient calculation. |
| calPerformance.auc.plot | Assess the performance obtained from the merged data set by independent validation |
| calPerformance.merge.indep | Assess performance derived from the merged data set by independent validation |
| calPerformance.meta | Meta analysis of survival data |
| calPerformance.single.indep | Performance assessment on single data sets using independent validation |
| ci.gm | Confidence interval of a Geometric mean |
| comb.surv.censor | Merge survival times and censoring status. |
| ComBat | ComBat-adjusted microarray gene expression data |
| combat.likelihood | Likelihood function. |
| compute.combat | Initiate ComBat adjustment |
| cross.val.combat | Cross validation with ComBat adjustment |
| cross.val.surv | Cross validation with or without Z-score normalization |
| design.mat | Build a design matrix |
| det.batchID | Determine the batch ID of data sets. |
| det.set.ind | Determine the indices of the training or testing set. |
| det.set.meta | Split data for meta analysis. |
| detFileName | Determine the name of a file. |
| eval.merge.simulate | Performance evaluation by merging two simulated independent data sets |
| eval.subset | Performance evaluation derived from a subset of a data set |
| excl.missing | Exclude missing samples |
| excl.missing.single.indep | Exclude missing samples prior to independent validation |
| excl.samples | Exclude samples |
| featureselection | Apply a feature selection |
| featureselection.meta | Feature selection for meta analysis |
| filter.absent | Filter absent calls |
| generate.survival.data | Generate survival data. |
| gm | Geometric Mean |
| groups.cv | Split a data set for cross-validation |
| init.plot | Start plotting |
| int.eprior | Integration function to find nonparametric adjustments |
| inv.normal | Apply the inverse normal method. |
| it.sol | Iterative solution for Empirical Bayesian method. |
| iter.crossval | Performance assessment of gene signatures by cross-validation. |
| iter.crossval.combat | Merge data set by ComBat within cross-validation. |
| iter.subset | Performance evaluation by subsetting data sets in 100 iterations |
| L | Likelihood function. |
| list.batch | Make a list of data batches. |
| main.merge.indep.valid | Performance assessment of merged data sets by independent validation |
| main.process | main.process |
| main.single.indep.valid | Independent validation of the performance of the gene signatures derived from single data sets. |
| meta.main | Meta analysis of survival data. |
| plot.roc.curves | Plot ROC curves of the testing set normalized by a joint analysis method. |
| plot.time.dep | Plot time-dependent ROC curves from 0 to 120 months. |
| plotROC | Plot ROC curves related to different time points. |
| pool.zscores | Combine data for meta analysis. |
| postmean | Estimated additive batch effect |
| postvar | Estimated multiplicative batch effect |
| pred.time.indep.valid | Prediction of survival time by independent validation. |
| prepcombat | Combination of data sets prior to the application of ComBat. |
| prepcombat.single.indep | Pair-wise combination of single data sets prior to the application of ComBat and independent validation. |
| prepzscore | Z-score normalization. |
| prepzscore1 | Apply Z-score1 normalization. |
| prepzscore2 | Apply Z-score2 normalization. |
| proc.simulate | Simulate survival data. |
| shuffle.samples | Shuffle samples. |
| splitMerged.auc.plot | Determine the indices of the training and testing sets. |
| splitMerged.indep | Merge the data sets by ComBat or Z-score1 normalization and apply independent validation. |
| splitZscore2.auc.plot | Z-score2 normalization prior to AUC plot. |
| splitZscore2.merge.indep | Merge data sets by Z-score2 normalization and assess the performance by independent validation. |
| trim.dat | Trim the data. |
| writeGeno | Reformat gene expression data for ComBat. |
| writeSamples | Write batch samples for ComBat. |
| znorm | Matrix Z-score normalization. |