sigCheckKnown {SigCheck} | R Documentation |
Performance of a signature is compared to performance of a panel of known (previously identified) signature.
sigCheckKnown(check, known="cancer")
check |
A |
known |
Either a character string specifying which set of signatures to use from the
included sets in |
Each specified known signature will be evaluated in the same manner as the primary signature. If survival data were supplied, a survival analysis will be carried out on the validation samples, and a p-value computed as a performance measure. If no survival data are available, the training samples will be used to train a classifier, and the performance score will be percentage of validation samples correctly classified. (If no validation samples are provided, leave-one-out cross validation will be used to calculate the classification performance for each known signature).
An empirical p-value will be computed based on the percentile rank of the performance of the primary signature compared to a null distribution of the performance of the known signatures.
A result list with the following elements:
$checkType
is equal to "Known"
.
$knownSigs
is the number of tests run (equal to the
number of known signatures indicated where at least one gene matches
a feature).
$rank
is the performance rank of the primary signature
within the performance of the known signatures.
$checkPval
is the empirical p-value computed using the scores
of the known signature as a null distribution. A value of zero indicates that
no known signatures performed as good or better than the primary signature.
$survivalPval
represents the performance of the primary signature,
if survival data were provided.
$survivalPvalsKnown
is a vector of performance scores (p-values)
for each known signature on the validation samples, if survival data
were provided.
$trainingPvalsKnown
is a vector of performance scores (p-values)
for each known signature on the training samples, if survival data
and separate validation samples were provided.
$sigPerformance
is the proportion of validation samples
correctly classified by the primary signature if a classifier was used.
$modePerformance
is the proportion of validation samples
correctly classified using a mode classifier.
$performanceKnown
is a vector of classification performance
scores for each
known signature, each indicating the proportion
of validation samples correctly classified is a classifier was used.
Rory Stark
Venet, David, Jacques E. Dumont, and Vincent Detours. "Most random gene expression signatures are significantly associated with breast cancer outcome." PLoS Computational Biology 7.10 (2011): e1002240.
knownSignatures
, sigCheck
,
sigCheckAll
, sigCheckRandom
,
sigCheckPermuted
, sigCheckPlot
#Disable parallel so Bioconductor build won't hang library(BiocParallel) register(SerialParam()) library(breastCancerNKI) data(nki) nki <- nki[,!is.na(nki$e.dmfs)] data(knownSignatures) ## survival analysis check <- sigCheck(nki, classes="e.dmfs", survival="t.dmfs", signature=knownSignatures$cancer$VANTVEER, annotation="HUGO.gene.symbol", validationSamples=150:319) knownResult <- sigCheckKnown(check) knownResult$checkPval knownResult$survivalPvalsKnown[knownResult$survivalPvalsKnown < knownResult$checkPval] sigCheckPlot(knownResult)