AggregateMC: Aggregation of repeated rankings using a Markov chain...

In GeneSelector: Stability and Aggregation of ranked gene lists

Description

All obtained rankings are aggregated on the basis of Markov chain model, in which each gene constitutes an element of the state space. For details, see DeConde et al. (2006).

Usage

  AggregateMC(RR, maxrank, type=c("MC4", "MCT"), epsilon = 0.15)

Arguments

RR	An object of class RepeatedRanking.
maxrank	Due to time- and memory requirements, the computation is limited to a reduced set of candidate genes. A gene is selected as candidate only if at least of one its ranks is smaller than or equal to maxrank. The remainder is assigned the rank maxrank+1 as rank after aggregation.
type	Specifies the computation of the matrix of transition probabilities. If type = "MC4", the transition probabilities are forced to be binary, while they may principally range from zero to one if type = "MCT", see DeConde et al. (2006) for details.
epsilon	A second parameter concerning the computation of the transition matrix, necessary to guarantee ergodicity and hence existence of a unique stationary distribution of the Markov chain. The value epsilon = 0.15, 0 < epsilon < 1, is recommended in DeConde et al. (2006).

Value

An object of class AggregatedRanking.

Author(s)

Martin Slawski
Anne-Laure Boulesteix

References

DeConde, R. P., Hawley, S., Falcon, S., Clegg, N., Knudsen, B., Etzioni, R. (2006).
Combining results of microarray experiments: a rank aggregation approach. Statistical Applications in Genetics and Molecular Biology 5, 15

See Also

RepeatRanking, AggregateSVD, AggregatePenalty, AggregateSimple

Examples

## Load toy gene expression data
data(toydata)
### class labels
yy <- toydata[1,]
### gene expression
xx <- toydata[-1,]
### run RankingTstat
ordT <- RankingTstat(xx, yy, type="unpaired")
### Generate Leave-one-out Foldmatrix
loo <- GenerateFoldMatrix(y = yy, k=1)
### Get all rankings
loor_ordT <- RepeatRanking(ordT, loo)
### aggregate rankings
agg_MC_ordT <- AggregateMC(loor_ordT, type = "MCT", maxrank = 100)
toplist(agg_MC_ordT)

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, 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")'.

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5      5
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8     38
9     28
10    40

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