GetStabilityGLM {GeneSelector} | R Documentation |
Assesses the stability of the set of genes declared statistically significant for differential expression. To this end, p-values or adjusted p-values are used to generate binary response variables for a logistic regression model. As single covariate, the ranks obtained from the original dataset are used. Analogously to the linear model approach, weights are incorporated to attribute more importance to higher ranked genes. The deviance(s) resulting from these models are used as stability measure.
GetStabilityGLM(RR, decay = c("linear", "quadratic", "exponential"), scheme = c("rank", "pval"), alpha = 1, maxpval = 0.05, method=c("raw", "BH", "qvalue", "Bonferroni", "Holm", "Hochberg", "SidakSS", "SidakSD", "BY"))
RR |
An object of class RepeatRanking. |
scheme |
Whether ranks (scheme="rank" ) or p-values (scheme="pval" )
should be used as basis of weighting. |
decay |
argument controlling the weight decay for the weights
used in the linear regression model. If decay=linear ,
then the weight of the s-th rank/p-value is 1/s ,
if decay=quadratic , then the weight is 1/s^2
and if decay=exponential , then the weight is exp(-s*alpha) ,
where alpha is a tuning parameter specified via
the argument alpha . |
alpha |
To be specified only if decay="exponential" , s. also
GetAlpha. |
maxpval |
The maximum p-value that is still considered significant (type I error). Default is 0.05. |
method |
The method used for p-value adjustment, s. AdjustPvalues.
If method = "raw" , then the raw p-values will be used. |
An object of class GetStabilityGLM
Martin Slawski martin.slawski@campus.lmu.de
Anne-Laure Boulesteix http://www.slcmsr.net/boulesteix
GetRepeatRanking, GetStabilityLm, GetStabilityOverlap, GetStabilityPCA, RecoveryScore, GetAlpha