Survival Prediction by Joint Analysis of Microarray Gene Expression Data


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Documentation for package ‘survJamda’ version 1.1.4

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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.