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

 Package: RGMQL

 Type: Package

 Title: GenoMetric Query Language for R/Bioconductor

-Version: 0.99.4

+Version: 0.99.5

 Author: Simone Pallotta, Marco Masseroli

 Maintainer: Simone Pallotta <simonepallotta@hotmail.com>

 Description: This package brings GMQL functionalities into R environemnt.

@@ -22,7 +22,7 @@ Encoding: UTF-8

 LazyData: true

 RoxygenNote: 6.0.1

 Imports: httr, rJava,GenomicRanges, rtracklayer, data.table, utils, plyr, xml2, methods, S4Vectors, dplyr, stats

-Depends: R(>= 3.3.3)

+Depends: R(>= 3.4.0)

 VignetteBuilder: knitr

 Suggests: BiocStyle, knitr, rmarkdown

 biocViews: Software,Infrastructure,DataImport

@@ -26,8 +26,10 @@

 #'

 importGMQL.gtf <- function(datasetName)

 {

-  datasetName <- paste0(datasetName,"/files")

-

+  datasetName <- sub("/*[/]$","",datasetName)

+  if(basename(datasetName) !="files")

+    datasetName <- paste0(datasetName,"/files")

+  

   if(!dir.exists(datasetName))

     stop("Directory does not exists")

@@ -86,7 +88,9 @@ importGMQL.gtf <- function(datasetName)

 #'

 importGMQL.gdm <- function(datasetName)

 {

-  datasetName <- paste0(datasetName,"/files")

+  datasetName <- sub("/*[/]$","",datasetName)

+  if(basename(datasetName) !="files")

+    datasetName <- paste0(datasetName,"/files")

   if(!dir.exists(datasetName))

     stop("Directory does not exists")

@@ -154,6 +154,9 @@ readDataset <- function(dataset, parser = "CustomParser", is_local=TRUE,

 #'

 #'

 #' @importFrom S4Vectors metadata

+#' @importFrom rJava J

+#' @importFrom rJava .jarray

+#' 

 #' @param samples GrangesList

 #' 

 #'

@@ -171,9 +174,14 @@ read <- function(samples)

     stop("only GrangesList")

   meta <- S4Vectors::metadata(samples)

-  if(is.null(meta)) {

+  if(is.null(meta) || length(meta)==0) {

+    #repeat meta for each sample in samples list

+    len <- length(samples)

     warning("GrangesList has no metadata. we provide two metadata for you")

-    meta_matrix <- matrix(c("Provider","Polimi", "Application", "R-GMQL"),ncol = 2,byrow = TRUE)

+    index_meta <- rep(1:len,each = len)

+    rep_meta <- rep(c("Provider","Polimi", "Application", "R-GMQL"),times=len)

+    meta_matrix <- matrix(rep_meta,ncol = 2,byrow = TRUE)

+    meta_matrix <- cbind(index_meta,meta_matrix)

   }

   else {

     unlist_meta <- unlist(meta)

@@ -185,7 +193,8 @@ read <- function(samples)

   df <- data.frame(samples)

   df <- df[-2] #delete group_name

   region_matrix <- as.matrix(sapply(df, as.character))

-  region_matrix<- region_matrix[,setdiff(colnames(region_matrix),"width")]

+  region_matrix[is.na(region_matrix)] <- "NA"

+  region_matrix <- region_matrix[,setdiff(colnames(region_matrix),"width")]

   col_types <- sapply(df,class)

   col_names <- names(col_types)

   #re order the schema?

@@ -203,6 +212,12 @@ read <- function(samples)

   }

   rownames(schema_matrix) <- NULL

   colnames(schema_matrix) <- NULL

+  

+  schema_matrix <- .jarray(schema_matrix,dispatch = TRUE)

+  meta_matrix <- .jarray(meta_matrix,dispatch = TRUE)

+  region_matrix <- .jarray(region_matrix,dispatch = TRUE)

+  

+

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

   response <- WrappeR$read(meta_matrix,region_matrix,schema_matrix)

   DAGgraph(response)

@@ -233,7 +248,9 @@ read <- function(samples)

 #' 

 #' @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

-#'

+#' 

+#' @return None

+#' 

 #' @examples

 #' 

 #' # initialize with remote processing off

@@ -2,8 +2,8 @@

 #  source("https://bioconductor.org/biocLite.R")

 #  biocLite("RGMQL")

-## ---- initialization, eval=FALSE-----------------------------------------

-#  library('RGMQL')

+## ---- initialization, eval=TRUE------------------------------------------

+library('RGMQL')

 ## ---- init, eval=FALSE---------------------------------------------------

 #  initGMQL()

@@ -21,6 +21,7 @@

 #  data_out = readDataset("dataset_name_on_repo")

 ## ---- read GRangesList, eval=FALSE---------------------------------------

+#  library("GenomicRanges")

 #  gr1 <- GRanges(seqnames = "chr2",

 #  ranges = IRanges(103, 106),

 #  strand = "+",

@@ -62,9 +63,9 @@ library("RGMQL")

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

 login.GMQL(test_url)

-## ---- eval=FALSE---------------------------------------------------------

-#  test_url = "http://130.186.13.219/gmql-rest"

-#  login.GMQL(test_url)

-#  runQuery(test_url, "query_1", "DATA_SET_VAR = SELECT() HG19_TCGA_dnaseq;

-#           MATERIALIZE DATA_SET_VAR INTO RESULT_DS;", output_gtf = FALSE)

+## ---- eval=TRUE----------------------------------------------------------

+test_url = "http://130.186.13.219/gmql-rest"

+login.GMQL(test_url)

+runQuery(test_url, "query_1", "DATA_SET_VAR = SELECT() HG19_TCGA_dnaseq; 

+         MATERIALIZE DATA_SET_VAR INTO RESULT_DS;", output_gtf = FALSE)

@@ -84,7 +84,7 @@ managing datasets (both GMQL or generic text plain dataset).

 ### Initialization

 Load and attach the GMQL package in an R session using library function:

-```{r, initialization, eval=FALSE}

+```{r, initialization, eval=TRUE}

 library('RGMQL')

 ```

 Before starting using any GMQL operation we need to initialise the GMQL context 

@@ -128,6 +128,7 @@ There is no need to explicitally download data since execution will trigger down

 Also, for better integration in R environment and with other packages, we provide a function

 to read from GrangesList, for example:

 ```{r, read GRangesList, eval=FALSE}

+library("GenomicRanges")

 gr1 <- GRanges(seqnames = "chr2",

 ranges = IRanges(103, 106),

 strand = "+",

@@ -223,7 +224,7 @@ wit this token you can call all the funciton in web services suite.

 #### Execution

 User can write the query as in the following example, as the second parameter of *runQuery*.

-```{r, eval=FALSE}

+```{r, eval=TRUE}

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

 login.GMQL(test_url)

 runQuery(test_url, "query_1", "DATA_SET_VAR = SELECT() HG19_TCGA_dnaseq; 

Binary files a/inst/doc/my-vignette.pdf and b/inst/doc/my-vignette.pdf differ

Binary files a/inst/java/GMQL.jar and b/inst/java/GMQL.jar differ

@@ -10,6 +10,9 @@ remote_processing(is_remote)

 \item{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}

 }

+\value{

+None

+}

 \description{

 It allows to enable or disable remote processing

 }

@@ -84,7 +84,7 @@ managing datasets (both GMQL or generic text plain dataset).

 ### Initialization

 Load and attach the GMQL package in an R session using library function:

-```{r, initialization, eval=FALSE}

+```{r, initialization, eval=TRUE}

 library('RGMQL')

 ```

 Before starting using any GMQL operation we need to initialise the GMQL context 

@@ -127,7 +127,8 @@ There is no need to explicitally download data since execution will trigger down

 4. GrangesList:\newline

 Also, for better integration in R environment and with other packages, we provide a function

 to read from GrangesList, for example:

-```{r, read GRangesList, eval=FALSE}

+```{r, read GRangesList, eval=TRUE}

+library("GenomicRanges")

 gr1 <- GRanges(seqnames = "chr2",

 ranges = IRanges(103, 106),

 strand = "+",

@@ -223,7 +224,7 @@ wit this token you can call all the funciton in web services suite.

 #### Execution

 User can write the query as in the following example, as the second parameter of *runQuery*.

-```{r, eval=FALSE}

+```{r, eval=TRUE}

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

 login.GMQL(test_url)

 runQuery(test_url, "query_1", "DATA_SET_VAR = SELECT() HG19_TCGA_dnaseq;