version 1.1.4

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: PharmacoGx
 Type: Package
 Title: Analysis of Large-Scale Pharmacogenomic Data
-Version: 1.1.2
-Date: 2015-11-13
+Version: 1.1.4
+Date: 2016-01-07
 Author: Petr Smirnov, Zhaleh Safikhani, Benjamin Haibe-Kains
 Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains@utoronto.ca>
 Description: Contains a set of functions to perform large-scale analysis of pharmacogenomic data.
@@ -11,8 +11,11 @@ Suggests: xtable
 Encoding: UTF-8
 Imports: Biobase, piano, magicaxis, RColorBrewer, parallel, caTools,
         methods, downloader, stats, utils, graphics, grDevices
-Depends: R (>= 2.10)
+Depends: R (>= 3.2)
+RoxygenNote: 5.0.1
+biocViews: GeneExpression, Pharmacogenetics, Pharmacogenomics, Software
+BugReports: https://github.com/bhklab/PharmacoGx/issues
 NeedsCompilation: no
-Packaged: 2015-11-14 18:15:28 UTC; bhaibeka
+Packaged: 2016-01-08 03:20:24 UTC; bhaibeka
 Repository: CRAN
-Date/Publication: 2015-11-15 10:08:46
+Date/Publication: 2016-01-08 08:49:25

MD5

@@ -1,106 +1,106 @@
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 59af8835692df3a4717f32869615bbca *vignettes/CreatingPharmacoSet-concordance.tex
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 31bd0238b7785475cfebdcaeaf8cda37 *vignettes/CreatingPharmacoSet.tex
-4b32434639f9eefba19ad8233b37be0f *vignettes/PharmacoGx.Rnw
+02c220c81e32ae240faeb085e9713676 *vignettes/PharmacoGx.Rnw
 0a1c145a5ef73983dbbf130e0ced5379 *vignettes/biblio.bib
 b62b07b83dd4f275fd9eab4e7e9bd0fc *vignettes/pharmacogx.bib

NAMESPACE

@@ -1,4 +1,4 @@
-# Generated by roxygen2 (4.1.1): do not edit by hand
+# Generated by roxygen2: do not edit by hand
 
 export(PharmacoSet)
 export(availablePSets)
@@ -67,6 +67,7 @@ importFrom(graphics,par)
 importFrom(graphics,plot)
 importFrom(graphics,points)
 importFrom(graphics,rect)
+importFrom(magicaxis,magaxis)
 importFrom(piano,loadGSC)
 importFrom(piano,runGSA)
 importFrom(stats,anova)

R/GWC.R

@@ -4,21 +4,30 @@
 ########################
 
 #################################################
-#' Calculate the gwc score between two vectors, using either a weighted spearman or pearson correlation
+#'Calculate the gwc score between two vectors, using either a weighted spearman or pearson correlation
 #'
-#'  @param x1 \code{numeric} vector of effect sizes (e.g., fold change or t statitsics) for the first experiment
-#'  @param p1 \code{numeric} vector of p-values for each corresponding effect size for the first experiment
-#'  @param x2 \code{numeric} effect size (e.g., fold change or t statitsics) for the second experiment
-#'  @param p2 \code{numeric} vector of p-values for each corresponding effect size for the second experiment
-#'  @param nperm \code{numeric} how many permutations should be done to determine
-#'  @param method.cor \code{character} string identifying if a \code{pearson} or
-#'    \code{spearman} correlation should be used
-#'  @param ... Other passed down to internal functions
+#'@examples
+#'data(CCLEsmall)
+#'x <- molecularProfiles(CCLEsmall,"rna")[,1]
+#'y <- molecularProfiles(CCLEsmall,"rna")[,2]
+#'x_p <- rep(0.05, times=length(x))
+#'y_p <- rep(0.05, times=length(y))
+#'names(x_p) <- names(x)
+#'names(y_p) <- names(y)
+#'gwc(x,x_p,y,y_p, nperm=100)
 #'
-#' @return \code{numeric} a vector of two values, the correlation and associated p-value.
-#'
-#' @export
-##			-
+#'@param x1 \code{numeric} vector of effect sizes (e.g., fold change or t statitsics) for the first experiment
+#'@param p1 \code{numeric} vector of p-values for each corresponding effect size for the first experiment
+#'@param x2 \code{numeric} effect size (e.g., fold change or t statitsics) for the second experiment
+#'@param p2 \code{numeric} vector of p-values for each corresponding effect size for the second experiment
+#'@param nperm \code{numeric} how many permutations should be done to determine
+#'@param method.cor \code{character} string identifying if a \code{pearson} or 
+#'\code{spearman} correlation should be used
+#'@param ... Other passed down to internal functions
+#'  
+#'@return \code{numeric} a vector of two values, the correlation and associated p-value.
+#'@export
+##            -
 ##
 ## http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient#Calculating_a_weighted_correlation
 ## http://www.mathworks.com/matlabcentral/fileexchange/20846-weighted-correlation-matrix