RankingLimma: Ranking based on the 'moderated' t statistic

In GeneSelector: Stability and Aggregation of ranked gene lists

Description

The 'moderated' t statistic is based on a Bayesian hierarchical model which is estimated by an empirical Bayes approach (Smyth et al., 2003). The function is a wrapper to the functions fitLm and eBayes implemented in the limma package.

Usage

RankingLimma(x, y, type = c("unpaired", "paired", "onesample"), gene.names = NULL, ...)

Arguments

x	A matrix of gene expression values with rows corresponding to genes and columns corresponding to observations or alternatively an object of class ExpressionSet. If type = paired, the first half of the columns corresponds to the first measurements and the second half to the second ones. For instance, if there are 10 observations, each measured twice, stored in an expression matrix expr, then expr[,1] is paired with expr[,11], expr[,2] with expr[,12], and so on.
y	If x is a matrix, then y may be a numeric vector or a factor with at most two levels. If x is an ExpressionSet, then y is a character specifying the phenotype variable in the output from pData. If type = paired, take care that the coding is analogously to the requirement concerning x
type	"unpaired": two-sample test. "paired": paired test. Take care that the coding of y is correct (s. above) "onesample": y has only one level. Test whether the true mean is different from zero.
gene.names	An optional vector of gene names.
...	Further arguments passed to the function eBayes, for instance the prior probability for differential expression. Consult the help of the limma package for details

Value

An object of class GeneRanking.

Author(s)

Martin Slawski
Anne-Laure Boulesteix

References

Smyth, G. K., Yang, Y.-H., Speed, T. P. (2003).
Statistical issues in microarray data analysis. Methods in Molecular Biology 2:24, 111-136.

See Also

RepeatRanking, RankingTstat, RankingFC, RankingWelchT, RankingWilcoxon, RankingBaldiLong, RankingFoxDimmic, RankingEbam, RankingWilcEbam, RankingSam, RankingShrinkageT, RankingSoftthresholdT, RankingPermutation

Examples

### Load toy gene expression data
data(toydata)
### class labels
yy <- toydata[1,]
### gene expression
xx <- toydata[-1,]
### run RankingLimma
limma <- RankingLimma(xx, yy, type="unpaired")

Example output

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, basename, cbind, colMeans, colSums, colnames,
    dirname, 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")'.


Attaching package: 'limma'

The following object is masked from 'package:BiocGenerics':

    plotMA

GeneSelector documentation built on May 1, 2019, 11:35 p.m.