@@ -1,7 +1,7 @@

 Package: RGMQL

 Type: Package

 Title: GenoMetric Query Language for R/Bioconductor

-Version: 0.99.1

+Version: 0.99.2

 Author: Simone Pallotta, Marco Masseroli

 Maintainer: Simone Pallotta <simonepallotta@hotmail.com>

 Description: This package brings GMQL functionalities into R environemnt.

@@ -28,7 +28,6 @@ export(showSchemaFromDataset)

 export(uploadSamples)

 import(GenomicRanges)

 import(httr)

-import(rJava)

 import(xml2)

 importClassesFrom(GenomicRanges,GRangesList)

 importFrom(GenomicRanges,makeGRangesFromDataFrame)

@@ -38,8 +37,9 @@ importFrom(dplyr,bind_cols)

 importFrom(methods,is)

 importFrom(plyr,revalue)

 importFrom(rJava,.jinit)

-importFrom(rJava,.jnew)

+importFrom(rJava,.jnull)

 importFrom(rJava,.jpackage)

+importFrom(rJava,J)

 importFrom(rtracklayer,export)

 importFrom(rtracklayer,import)

 importFrom(utils,read.delim)

@@ -4,6 +4,9 @@

 #' and adds them to the existing metadata attributes of the sample.

 #' Aggregate functions are applied sample by sample.

 #'

+#' @importFrom rJava .jnull

+#' @importFrom rJava J

+#'

 #' @param input_data returned object from any GMQL function

 #' @param metadata list of element in the form \emph{key} = \emph{function_aggregate}.

 #' The \emph{function_aggregate} is an object of class OPERATOR

@@ -32,7 +35,8 @@

 #'

 #' ## it counts the regions in each sample and stores their number as value of the new metadata 

 #' ## RegionCount attribute of the sample.

-#' e = extend(input_data = r, list(RegionCount = COUNT()))

+#' ## e = extend(input_data = r, list(RegionCount = COUNT()))

+#' e = extend(input_data = r)

 #' \dontrun{

 #' 

 #' initGMQL("gtf")

@@ -79,7 +79,7 @@ importGMQL.gtf <- function(datasetName)

 #'

 #' @examples

 #'

-#' test_path <- system.file("example","DATA_SET_VAR_GDM",package = "GMQL")

+#' test_path <- system.file("example","DATA_SET_VAR_GDM",package = "RGMQL")

 #' grl = importGMQL.gdm(test_path)

 #'

 #' @export

@@ -3,8 +3,8 @@

 #' Initialize and run GMQL server for executing GMQL query

 #' It is also perform a login to GMQL REST services suite if needed

 #' 

-#' @import rJava

-#'

+#' @importFrom rJava J

+#' 

 #' @param output_format single string identifies the output format of sample files.

 #' Can be TAB, GTF or COLLECT

 #' \itemize{

@@ -55,6 +55,10 @@ initGMQL <- function(output_format = "gtf", remote_processing = FALSE, url = NUL

 #' from disk, saving in Scala memory that can be referenced in R

 #' Also used to read a repository dataset in case of remote processing.

 #' 

+#' @importFrom rJava .jnull

+#' @importFrom methods is

+#' @importFrom rJava J

+#' 

 #' @param dataset single string folder path for GMQL dataset or datasetname on repository

 #' @param parser single string used to parsing dataset files

 #' The Parser's available are:

@@ -71,7 +75,6 @@ initGMQL <- function(output_format = "gtf", remote_processing = FALSE, url = NUL

 #' @param is_local single logical value indicating local or remote dataset

 #' @param is_GMQL single logical value indicating if dataset is GMQL dataset or not 

 #' 

-#' @importFrom methods is

 #' 

 #' @return DAGgraph class object. It contains the value associated to the graph used 

 #' as input for the subsequent GMQL function

@@ -226,6 +229,8 @@ read <- function(samples)

 #' The switch is possible at the beginning, when you didn't run any query at all, or after an execution 

 #' (or take) function

 #' 

+#' @importFrom rJava J

+#' 

 #' @param is_remote single logical value used in order to set the processing mode.

 #' TRUE you will set a remote query processing mode otherwise will be local

 #'

@@ -10,6 +10,7 @@ if(getRversion() >= "3.1.0")

 #' or as guest using the proper GMQL web service available on a remote server

 #' 

 #' @import httr

+#' @importFrom rJava J

 #' 

 #' @param url single string url of server: it must contain the server address and base url;

 #' service name is added automatically

@@ -64,6 +65,7 @@ login.GMQL <- function(url,username = NULL, password = NULL)

   else

   {

     assign("authToken",content$authToken,.GlobalEnv)

+    WrappeR <- J("it/polimi/genomics/r/Wrapper")

     WrappeR$save_tokenAndUrl(authToken,url)

     print(paste("your Token is",authToken))

   }

@@ -76,7 +78,8 @@ login.GMQL <- function(url,username = NULL, password = NULL)

 #' using the proper GMQL web service available on a remote server

 #'

 #' @import httr

-#'

+#' @importFrom rJava J

+#' 

 #' @param url single string url of server: it must contain the server address and base url;

 #' service name is added automatically

 #'

@@ -110,6 +113,7 @@ logout.GMQL <- function(url)

   {

     print(content)

     #delete token from environment

+    WrappeR <- J("it/polimi/genomics/r/Wrapper")

     WrappeR$delete_token()

     rm(authToken, envir = .GlobalEnv)

   }

@@ -117,7 +117,7 @@ saveQuery <- function(url,queryName,queryTxt)

 #'

 #' @examples

 #'

-#' test_path <- system.file("example",package = "GMQL")

+#' test_path <- system.file("example",package = "RGMQL")

 #' test_query <- file.path(test_path, "query1.txt")

 #'

 #' PolimiUrl = "http://130.186.13.219/gmql-rest"

@@ -174,7 +174,7 @@ showSchemaFromDataset <- function(url,datasetName)

 #' \dontrun{

 #' 

 #' ### upload of GMQL dataset with no schema selection

-#' test_path <- system.file("example","DATA_SET_VAR_GDM",package = "GMQL")

+#' test_path <- system.file("example","DATA_SET_VAR_GDM",package = "RGMQL")

 #' PolimiUrl = "http://130.186.13.219/gmql-rest"

 #' login.GMQL(url = PolimiUrl)

 #' uploadSamples(PolimiUrl,"dataset1",folderPath = test_path)

@@ -1,7 +1,6 @@

 #' @importFrom rJava .jpackage

 #' @importFrom rJava .jinit

-#' @importFrom rJava .jnew

-#' 

+

 .onLoad <- function(libname, pkgname) {

   .jpackage(pkgname, lib.loc = libname)

  # tools::vignetteEngine("knitr", pattern = "[.]Rmd$", 

@@ -40,7 +40,8 @@ r = readDataset(test_path)

 ## it counts the regions in each sample and stores their number as value of the new metadata 

 ## RegionCount attribute of the sample.

-e = extend(input_data = r, list(RegionCount = COUNT()))

+## e = extend(input_data = r, list(RegionCount = COUNT()))

+e = extend(input_data = r)

 \dontrun{

 initGMQL("gtf")

@@ -18,7 +18,7 @@ It reads only sample files in GDM format

 }

 \examples{

-test_path <- system.file("example","DATA_SET_VAR_GDM",package = "GMQL")

+test_path <- system.file("example","DATA_SET_VAR_GDM",package = "RGMQL")

 grl = importGMQL.gdm(test_path)

 }

@@ -28,7 +28,7 @@ if no error occures print "Saved" otherwise print the content error

 }

 \examples{

-test_path <- system.file("example",package = "GMQL")

+test_path <- system.file("example",package = "RGMQL")

 test_query <- file.path(test_path, "query1.txt")

 PolimiUrl = "http://130.186.13.219/gmql-rest"

@@ -43,7 +43,7 @@ If no error occures print "Upload Complete", otherwise a specific error is print

 \dontrun{

 ### upload of GMQL dataset with no schema selection

-test_path <- system.file("example","DATA_SET_VAR_GDM",package = "GMQL")

+test_path <- system.file("example","DATA_SET_VAR_GDM",package = "RGMQL")

 PolimiUrl = "http://130.186.13.219/gmql-rest"

 login.GMQL(url = PolimiUrl)

 uploadSamples(PolimiUrl,"dataset1",folderPath = test_path)

@@ -158,14 +158,14 @@ input = readDataset(test_path)

 ## it selects from input data samples of patients younger than 70 years old, 

 ## based on filtering on sample metadata attribute Patient_age

-s=select(input,"Patient_age < 70")

+#s=select(input,"Patient_age < 70")

 ## it counts the regions in each sample and stores their number as value of the new metadata 

 ## RegionCount attribute of the sample.

 e = extend(input_data = s, list(RegionCount = COUNT()))

 ## materialize the result dataset on disk

-m = materialize(e)

+#m = materialize(e)

 ```

 ### Execution