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 survJamda: Survival Prediction by Joint Analysis of Microarray Gene Expression Data
 det.batchID: Determine the batch ID of data sets.
Determine the batch ID of data sets.
Description
Determine the batch ID of data sets for ComBat.
Usage
1  det.batchID(geno.files)

Arguments
geno.files 
A vector of character containing the names of gene expression data files. 
Value
A vector of integers specifying the batch ID of data sets. The integers from 1 to the number specifying the length of geno.files
are set as the batch ID of the data sets named in geno.files
as follows: 1 to the first expression file name in geno.files
, 2 to the second expression file name in geno.files
, ... and the integer specifying the length of geno.files
to the last expression file in geno.files
, respectively.
Author(s)
Haleh Yasrebi
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 aprior: Calculate empirical hyperprior values
 Beta.NA: Fit the L/S model in the presence of missing data values
 bprior: Calculate empirical hyperprior 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...
 calPerformance.merge.indep: Assess performance derived from the merged data set by...
 calPerformance.meta: Meta analysis of survival data
 calPerformance.single.indep: Performance assessment on single data sets using independent...
 ci.gm: Confidence interval of a Geometric mean
 ComBat: ComBatadjusted microarray gene expression data
 combat.likelihood: Likelihood function.
 comb.surv.censor: Merge survival times and censoring status.
 compute.combat: Initiate ComBat adjustment
 cross.val.combat: Cross validation with ComBat adjustment
 cross.val.surv: Cross validation with or without Zscore normalization
 design.mat: Build a design matrix
 det.batchID: Determine the batch ID of data sets.
 detFileName: Determine the name of a file.
 det.set.ind: Determine the indices of the training or testing set.
 det.set.meta: Split data for meta analysis.
 eval.merge.simulate: Performance evaluation by merging two simulated independent...
 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 crossvalidation
 init.plot: Start plotting
 int.eprior: Integration function to find nonparametric adjustments
 inv.normal: Apply the inverse normal method.
 iter.crossval: Performance assessment of gene signatures by...
 iter.crossval.combat: Merge data set by ComBat within crossvalidation.
 iter.subset: Performance evaluation by subsetting data sets in 100...
 it.sol: Iterative solution for Empirical Bayesian method.
 L: Likelihood function.
 list.batch: Make a list of data batches.
 main.merge.indep.valid: Performance assessment of merged data sets by independent...
 main.process: main.process
 main.single.indep.valid: Independent validation of the performance of the gene...
 meta.main: Meta analysis of survival data.
 plotROC: Plot ROC curves related to different time points.
 plot.roc.curves: Plot ROC curves of the testing set normalized by a joint...
 plot.time.dep: Plot timedependent ROC curves from 0 to 120 months.
 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: Pairwise combination of single data sets prior to the...
 prepzscore: Zscore normalization.
 prepzscore1: Apply Zscore1 normalization.
 prepzscore2: Apply Zscore2 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 Zscore1 normalization and...
 splitZscore2.auc.plot: Zscore2 normalization prior to AUC plot.
 splitZscore2.merge.indep: Merge data sets by Zscore2 normalization and assess the...
 survJamdapackage: Survival Prediction by Joint Analysis of Microarray Gene...
 trim.dat: Trim the data.
 writeGeno: Reformat gene expression data for ComBat.
 writeSamples: Write batch samples for ComBat.
 znorm: Matrix Zscore normalization.