Fisher.test: Fisher's combined probability method
In metaSeq: Meta-analysis of RNA-Seq count data in multiple studies

Description Usage Arguments Author(s) References See Also Examples

Fisher's method combines multiple p-values which are calculated in each study.

1	Fisher.test(pvals, na.mode = "notignore")

`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".

Koki Tsuyuzaki, Itoshi Nikaido

Fisher, R. A. (1932) Statistical Methods for Research Workers, 4th edition, Oliver and Boyd, London.

meta.readData, meta.oneside.noiseq, other.oneside.pvalues

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)

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

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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"