@@ -1,5 +1,5 @@

 Package: GSVA

-Version: 1.23.5

+Version: 1.23.6

 Title: Gene Set Variation Analysis for microarray and RNA-seq data

 Authors@R: c(person("Justin", "Guinney", role=c("aut", "cre"), email="justin.guinney@sagebase.org"),

              person("Robert", "Castelo", role="aut", email="robert.castelo@upf.edu"))

@@ -5,6 +5,19 @@ import(BiocGenerics)

 importClassesFrom(Biobase, ExpressionSet)

 importClassesFrom(GSEABase, GeneSetCollection)

+

+importMethodsFrom(Biobase, featureNames,

+                           phenoData,

+                           experimentData)

+

+importMethodsFrom(GSEABase, geneIds,

+                            incidence)

+

+importFrom(graphics, plot)

+importFrom(stats, ecdf,

+                  na.omit)

+importFrom(utils, setTxtProgressBar,

+                  txtProgressBar)

 importFrom(Biobase, exprs)

 importFrom(Biobase, annotation)

 importFrom(GSEABase, AnnoOrEntrezIdentifier)

@@ -97,8 +97,12 @@ Estimates GSVA enrichment scores.

                 while in the case of \code{plage} they are used to calculate the singular value decomposition

                 (SVD) over the genes in the gene set and use the coefficients of the first right-singular vector

                 as pathway activity profile.}

-  \item{rnaseq}{Flag to inform whether the input gene expression data comes from microarray

-                (\code{rnaseq=FALSE}, default) or RNA-Seq (\code{rnaseq=TRUE}) experiments.}

+  \item{rnaseq}{Logical flag set by default to \code{rnaseq=FALSE} to inform whether the input gene

+                expression data are continues values, such as fluorescent units in logarithmic scale

+                from microarray experiments or some other kind of continuous value derived from

+                RNA-seq counts such as log-CPMs, log-RPKMs or log-TPMs. This flag should be set to

+                \code{rnaseq=TRUE} only when the values of the input gene expression data are integer

+                counts.}

   \item{abs.ranking}{Flag to determine whether genes should be ranked according to 

   					their sign (\code{abs.ranking=FALSE}) or by absolute value (\code{abs.ranking=TRUE}). 

   					In the latter, pathways with genes enriched on either extreme

@@ -148,6 +152,16 @@ identifiers in the input expression data leading to a filtered collection of

 gene sets. This collection can be further filtered to require a minimun and/or

 maximum size of the gene sets for which we want to calculate GSVA enrichment

 scores, by using the arguments \code{min.sz} and \code{max.sz}.

+

+The name of the argument \code{rnaseq} can be misleading. When set to \code{rnaseq=FALSE}, the

+nonparametric estimation of the cumulative density function of the expression profile of

+each gene across samples is done using Gaussian kernels suited for continuous values. These were

+initially thought to be only microarray fluorescent units in logarithmic scale but nowadays these

+may also correspond to continuous values derived from RNA-seq experiments such as log-CPMs,

+log-RPKMs or log-TPMs. When \code{rnaseq=TRUE}, Poisson kernels are used instead and therefore,

+this option is only suitable when the input gene expression matrix is formed by integer counts.

+This implies that \code{rnaseq=FALSE} may also be used even when the expression data comes from

+a RNA-seq experiment. The name of this argument may change in the future to avoid this confusion.

 }

 \value{

 A gene-set by sample matrix of GSVA enrichment scores.