stabilityRanking {staRank} | R Documentation |
An S4 function to perform stability ranking on a dataset or directly on given sample rankings.
x |
the data that is to be ranked. It can be of different types: a data matrix with one row per element to be ranked, or a ranking from an external method, or an object of class cellHTS. Depending on this the other parameters can vary. |
samps |
a matrix of scored sample data, each row corresponds to an element, the columns to a scoring. This is only needed when an external ranking method is used. |
channel |
a string with the name of the feature (channel) to be ranked. This is only needed for cellHTS objects. |
replicates |
names or indices of the replicates (samples) to be used for the rankings (default: all samples are used). |
method |
one of the ranking methods: 'mean' (default), 'median', 'mwtest' (two-sample one sided Mann-Whitney test), 'ttest'(two-sample one sided t-test) or 'RSA' (redundant siRNA analysis). If an external ranking is used, you can specify the name of that ranking method in the method argument. |
decreasing |
a boolean indicating the direction of the ranking. |
bootstrap |
a boolean indicating if bootstrapping or subsampling is used. |
thr |
threshold for stability (default = 0.9). |
nSamp |
the number of samples to generate (default = 100). |
Pi |
boolean indicating if the Pi matrix should be returned (can be very large, default=FALSE). |
verbose |
boolean indicating if status update should be printed |
... |
further parameter for the stability ranking. |
an object of class RankSummary
.
# 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)