Description Usage Arguments Value Examples
View source: R/getRankmatrix.R
Extracts all three rankings from a RankSummary object.
1 | getRankmatrix(rs)
|
rs |
an object of class RankSummary. |
a ranking matrix where each row corresponds to one element and the columns give the ranks from stability, base and averaged ranking.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | # generate dataset
d<-replicate(4,sample(1:10,10,replace=FALSE))
rownames(d)<-letters[1:10]
# rank aggregation on the dataset using two base methods
aggregRank(d, method='mean')
aggregRank(d, method='median')
# calculate summary statistic from the data
summaryStats(d, method='mean')
summaryStats(d, method='RSA')
# calculating replicate scores from different summary statistics
scores<-getSampleScores(d,'mean',decreasing=FALSE,bootstrap=TRUE)
scores<-getSampleScores(d,'mwtest',decreasing=FALSE,bootstrap=TRUE)
# perform RSA analysis
# get RSA format of data
rsaData<-dataFormatRSA(d)
# set RSA options
opts<-list(LB=min(d),UB=max(d),reverse=FALSE)
# run the RSA analysis
r<-runRSA(rsaData,opts)
# directly obtain the per gene RSA ranking from the data
r<-uniqueRSARanking(rsaData,opts)
# get stable Ranking, stable setsizes and the Pi matrix for default settings
# and stability threshold of 0.9
s<-getStability(d,0.9)
# run default stability ranking
s<-stabilityRanking(d)
# using an accessor function on the RankSummary object
stabRank(s)
# summarize a RankSummary object
summary(s)
# generate a rank matrix from a RankSummary object
getRankmatrix(s)
|
Loading required package: cellHTS2
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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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a h d g i c e f j b
3.75 4.00 4.25 4.25 4.25 5.00 6.00 6.25 8.50 8.75
h a d c g i e f j b
3.0 3.5 4.0 4.5 4.5 5.0 6.0 6.5 8.5 9.0
a b c d e f g h i j
3.75 8.75 5.00 4.25 6.00 6.25 4.25 4.00 4.25 8.50
a b c d e f
-1.01371011 -0.09275405 -0.52306887 -1.65233426 -0.34896305 -0.40683372
g h i j
-0.93452887 -1.00000000 -1.09668435 -0.05281597
a g i c h d e f b j
1.0 2.5 2.5 4.5 4.5 6.5 6.5 8.0 9.5 9.5
Length Class Mode
1 RankSummary S4
mean_stability mean_base mean_averaged
a 1.0 1 1
g 2.5 4 3
i 2.5 4 2
c 4.5 6 6
h 4.5 2 4
d 6.5 4 5
e 6.5 7 7
f 8.0 8 8
b 9.5 10 10
j 9.5 9 9
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