Stouffer.test: Stouffer's weighted Z-score method (Inverse normal method)

Description Usage Arguments Author(s) References Examples

Description

Stouffer's method combines multiple weighted Z-scores which are calculated in each study. Although many weight can be introduced but weighting by sample-size is used in meta.oneside.noiseq.

Usage

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Stouffer.test(pvals, na.mode = "notignore")

Arguments

pvals

A matrix coming from meta.oneside.noiseq function or other.oneside.pvalues, which is used for any one-sided p-values or probability.

na.mode

A string indicating how to treat NA in pvals. "notignore" means that genes having at least one NA is regarded as NA. "ignore" means NA is ignored and remaining data is used. By default, na.mode = "notignore".

Author(s)

Koki Tsuyuzaki, Itoshi Nikaido

References

Stouffer, S. A. and Suchman, E. A. and DeVinney, L. C. and Star, S. A. and Williams, R. M. Jr. (1949) The American Soldier, Vol. 1 - Adjustment during Army Life. Princeton, Princeton University Press.

Examples

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data(BreastCancer)
library("snow")

# Experimental condition (1: BreastCancer, 0: Normal)
flag1 <- c(1,1,1,0,0, 1,0, 1,1,1,1,1,1,1,0, 1,1,0)

# Source of data
flag2 <- c("A","A","A","A","A", "B","B", "C","C","C","C","C","C","C","C", "D","D","D")

# readData function for meta-analysis
cds <- meta.readData(data = BreastCancer, factor = flag1, studies = flag2)

# oneside NOISeq for meta-analysis
# cl <- makeCluster(4, "SOCK")
# result <- meta.oneside.noiseq(cds, k = 0.5, norm = "tmm", replicates = "biological", factor = flag1, conditions = c(1, 0), studies = flag2, cl = cl)
# stopCluster(cl)

# Script above is very time-consumming step. Please use this pre-calculated result instead
data(Result.Meta)
result <- Result.Meta

# Fisher's method (without weighting)
F <- Fisher.test(result)
str(F)

# Stouffer's method (with weighting by sample-size)
S <- Stouffer.test(result)
str(S)

Example output

Loading required package: NOISeq
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: splines
Loading required package: Matrix
Loading required package: snow

Attaching package: 'snow'

The following objects are masked from 'package:BiocGenerics':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, clusterSplit, parApply, parCapply,
    parLapply, parRapply, parSapply

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, clusterSplit, makeCluster, parApply,
    parCapply, parLapply, parRapply, parSapply, splitIndices,
    stopCluster

Loading required package: Rcpp
List of 3
 $ Upper : Named num [1:23368] 0.384 0.532 0.533 NA 0.136 ...
  ..- attr(*, "names")= chr [1:23368] "1/2-SBSRNA4" "A1BG" "A1BG-AS1" "A1CF" ...
 $ Lower : Named num [1:23368] 0.842 0.608 0.405 NA 0.366 ...
  ..- attr(*, "names")= chr [1:23368] "1/2-SBSRNA4" "A1BG" "A1BG-AS1" "A1CF" ...
 $ Weight: Named int [1:4] 5 2 8 3
  ..- attr(*, "names")= chr [1:4] "Study 1" "Study 2" "Study 3" "Study 4"
List of 3
 $ Upper : Named num [1:23368] 0.371 0.266 0.271 NA 0.296 ...
  ..- attr(*, "names")= chr [1:23368] "1/2-SBSRNA4" "A1BG" "A1BG-AS1" "A1CF" ...
 $ Lower : Named num [1:23368] 0.629 0.734 0.729 NA 0.704 ...
  ..- attr(*, "names")= chr [1:23368] "1/2-SBSRNA4" "A1BG" "A1BG-AS1" "A1CF" ...
 $ Weight: Named int [1:4] 5 2 8 3
  ..- attr(*, "names")= chr [1:4] "Study 1" "Study 2" "Study 3" "Study 4"

metaSeq documentation built on Nov. 8, 2020, 7:26 p.m.