Description Usage Arguments Value Author(s) References Examples
This function calculates Zscore for each matched gene across all datasets. In each dataset, it performs local regression smoothing of mean vs variance. Z score is constructed by taking the ratio of weighted mean difference and combined standard deviation according to Box and Tiao (1992).
1 
merged 

pheno 
A numeric vector specifying the location of class labels in phenoData from each

permute 
If permute is 0, weighted Zscore will be referenced to standard normal distribution for twosided pvalue. Otherwise, columns of all datasets (each dataset separately) will be shuffled at random, from which a permutation distribution of Zscores are formed and Zscores are referenced to this distribution. 
verbose 
If verbose is TRUE, the progress of permutation will be reported. 
A data.frame with matched genes, Zscores and pvalues will result.
Debashis Ghosh <ghoshd@psu.edu>, Hyungwon Choi <hyung_won_choi@nuhs.edu.sg>
J.Wang et al, Bioinformatics 2004 Nov 22;20(17):316678
1  # Zscore(merged, pheno=NULL, permute=10000, verbose=FALSE)

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