\name{selectContrib} \alias{selectContrib} \alias{selectContrib,IcaSet-method} \alias{selectContrib,IcaSet,numeric,character-method} \alias{selectContrib,list,numeric,ANY} \alias{selectContrib,list,numeric,ANY-method} \title{Select contributing features/genes} \usage{ selectContrib(object, cutoff, level, ...) } \arguments{ \item{object}{Either an \code{IcaSet} object, or a list of projection vectors, e.g the list of feature or gene projections on each component.} \item{cutoff}{The threshold according to which the elements will be selected. Must be either of length 1 and the same treshold is applied to all components, or of length equal to the number of components in order to use a specific threshold for each component.} \item{level}{The level of the selection: either \code{"genes"} to select contributing genes using \code{SByGene(icaSet)}, or \code{"features"} to select contributing features using \code{S(icaSet)}. } \item{...}{...} } \value{ A list of projections restricted to the elements that are higher than \code{cutoff}. } \description{ This function selects elements whose absolute scaled values exceed a given threshold. } \details{ Each vector is first scaled and then only elements with an absolute scaled value higher than \code{cutoff} are kept. } \examples{ \dontrun{ ## load an example of icaSet data(icaSetCarbayo) ##### ========= #### When arg 'object' is an IcaSet object ##### ========= ## select contributing genes selectContrib(object=icaSetCarbayo, cutoff=3, level="genes") ## select contributing features selectContrib(object=icaSetCarbayo, cutoff=3, level="features") ##### ========= #### When arg 'object' is a list ##### ========= c1 <- rnorm(100); names(c1) <- 100:199 c2 <- rnorm(100); names(c2) <- 1:99 selectContrib(object=list(c1,c2), cutoff= 0.5) ## select contributing features contribFlist <- selectContrib(Slist(icaSetCarbayo), 3) ## select contributing genes contribGlist <- selectContrib(SlistByGene(icaSetCarbayo), 3) } } \author{ Anne Biton }