Browse code

manual and parser

Simone authored on 22/11/2017 23:06:08
Showing53 changed files

... ...
@@ -35,4 +35,4 @@ setMethod("show", "GMQLDataset",
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                 cat(" value :",paste(object@value))
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             })
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-#object <- as.list(substitute(list(...)))[-1L]
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+
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@@ -5,7 +5,7 @@
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 #' defined as input.
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 #' The metadata and metadata_prefix are used to filter the data and choose 
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 #' only the samples that match at least one metdatata with its prefix.
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-#' The regions are shown for each sample obtained from filtering.
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+#' The input regions are shown for each sample obtained from filtering.
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 #'
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 #' @import xml2
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 #' @importFrom dplyr bind_cols
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@@ -36,7 +36,6 @@
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 #'
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 #' @examples
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 #' 
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-#' \dontrun{
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 #' library(GenomicRanges)
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 #' gr1 <- GRanges(seqnames = "chr2", ranges = IRanges(3, 6), strand = "+", 
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 #' score = 5L, GC = 0.45)
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@@ -46,7 +45,8 @@
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 #' grl = GRangesList(gr1, gr2)
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 #' test_out_path <- system.file("example", package = "RGMQL")
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 #' export_gmql(grl, test_out_path,TRUE)
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-#' }
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+#' 
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+#' 
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 #' @export
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 #'
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 export_gmql <- function(samples, dir_out, is_gtf)
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@@ -158,7 +158,8 @@ take_value.META_AGGREGATES <- function(obj){
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 #' res = extend(exp, m_score = MEDIAN("score"))
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 #' 
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 #' 
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-#' @name AGGREGATES
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+#' @name SUM
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+#' @aliases SUM
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -172,7 +173,8 @@ SUM <- function(value)
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     return(list)
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 }
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-#' @name AGGREGATES
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+#' @name MIN
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+#' @aliases MIN
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -187,7 +189,8 @@ MIN <- function(value)
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 }
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-#' @name AGGREGATES 
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+#' @name MAX
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+#' @aliases MAX
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 #' @rdname aggr-class 
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 #' @export
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 #'
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@@ -201,7 +204,8 @@ MAX <- function(value)
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     return(list)
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 }
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-#' @name AGGREGATES
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+#' @name AVG
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+#' @aliases AVG
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -215,7 +219,8 @@ AVG <- function(value)
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     return(list)
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 }
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-#' @name AGGREGATES
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+#' @name BAG
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+#' @aliases BAG
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -229,7 +234,8 @@ BAG <- function(value)
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     return(list)
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 }
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-#' @name AGGREGATES
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+#' @name COUNT
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+#' @aliases COUNT
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -246,7 +252,8 @@ as.character.COUNT <- function(obj) {
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 }
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 check.COUNT <- function(obj){}
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-#' @name AGGREGATES
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+#' @name STD
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+#' @aliases STD
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -261,7 +268,8 @@ STD <- function(value)
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 }
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-#' @name AGGREGATES
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+#' @name MEDIAN
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+#' @aliases MEDIAN
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -275,7 +283,8 @@ MEDIAN <- function(value)
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     return(list)
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 }
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-#' @name AGGREGATES
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+#' @name Q1
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+#' @aliases Q1
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -289,7 +298,8 @@ Q1 <- function(value)
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     return(list)
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 }
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-#' @name AGGREGATES
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+#' @name Q2
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+#' @aliases Q2
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -302,7 +312,8 @@ Q2 <- function(value)
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     return(list)
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 }
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-#' @name AGGREGATES
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+#' @name Q3
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+#' @aliases Q3
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -316,7 +327,8 @@ Q3 <- function(value)
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     return(list)
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 }
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-#' @name AGGREGATES
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+#' @name BAGD
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+#' @aliases BAGD
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 #' @rdname aggr-class
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 #' @export
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 #'
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@@ -52,7 +52,8 @@ print.PARAMETER <- function(obj){
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 #' 
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 #' res = cover(exp, 2, ANY()+2/3)
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 #' 
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-#' @name COVER-PARAMETER
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+#' @name ALL
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+#' @aliases ALL
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 #' @rdname cover-param-class
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 #' @export
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 #'
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@@ -64,7 +65,8 @@ ALL <- function()
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     return(list)
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 }
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-#' @name COVER-PARAMETER
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+#' @name ANY
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+#' @aliases ANY
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 #' @rdname cover-param-class
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 #' @export
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 #'
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@@ -101,7 +101,8 @@ check.DISTAL <- function(value)
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 #' genometric_predicate = list(list(MD(1), DGE(12000), DOWN())), 
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 #' DF("provider"), region_output = "RIGHT")
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 #'
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-#' @name DISTAL
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+#' @name DL
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+#' @aliases DL
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 #' @rdname distal-class
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 #' @export
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 #' 
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@@ -114,7 +115,8 @@ DL <- function(value)
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     return(list)
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 }
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-#' @name DISTAL
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+#' @name DG
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+#' @aliases DG
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 #' @rdname distal-class
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 #' @export
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 #' 
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@@ -127,7 +129,8 @@ DG <- function(value)
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     return(list)
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 }
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-#' @name DISTAL
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+#' @name DLE
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+#' @aliases DLE
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 #' @rdname distal-class
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 #' @export
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 #' 
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@@ -140,7 +143,8 @@ DLE <- function(value)
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     return(list)
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 }
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-#' @name DISTAL
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+#' @name DGE
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+#' @aliases DGE
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 #' @rdname distal-class
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 #' @export
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 #' 
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@@ -153,7 +157,8 @@ DGE <- function(value)
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     return(list)
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 }
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-#' @name DISTAL
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+#' @name MD
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+#' @aliases MD
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 #' @rdname distal-class
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 #' @export
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 #' 
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@@ -167,7 +172,8 @@ MD <- function(value)
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 }
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-#' @name DISTAL
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+#' @name UP
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+#' @aliases UP
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 #' @rdname distal-class
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 #' @export
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 #' 
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@@ -184,7 +190,8 @@ as.character.UP <- function(obj) {
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 }
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-#' @name DISTAL
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+#' @name DOWN
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+#' @aliases DOWN
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 #' @rdname distal-class
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 #' @export
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 #' 
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@@ -87,7 +87,8 @@ as.character.OPERATOR <- function(obj) {
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 #' exp = read_dataset(test_path)
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 #' out = select(exp, metadata_update = list(concSq = SQRT("concentration")))
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 #' 
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-#' @name OPERATORS
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+#' @name META
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+#' @aliases META
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 #' @rdname operator-class
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 #' @export
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 #'
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@@ -122,7 +123,8 @@ check.META <- function(type)
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 }
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-#' @name OPERATORS
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+#' @name NIL
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+#' @aliases NIL
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 #' @rdname operator-class
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 #' @export
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 #'
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@@ -145,7 +147,8 @@ check.NIL <- function(value)
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 }
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-#' @name OPERATORS
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+#' @name SQRT
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+#' @aliases SQRT
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 #' @rdname operator-class
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 #' @export
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 #'
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@@ -29,7 +29,8 @@
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 #' test_path <- system.file("example", "DATASET", package = "RGMQL")
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 #' r = read_dataset(test_path)
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 #' 
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-#' @name evaluation
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+#' @name FN
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+#' @aliases FN
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 #' @rdname condition_eval_func
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 #' @export
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 FN <- function(...)
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@@ -49,7 +50,8 @@ FN <- function(...)
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     join_condition_matrix
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 }
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-#' @name evaluation
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+#' @name EX
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+#' @aliases EX
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 #' @rdname condition_eval_func
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 #' @export
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 EX <- function(...)
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@@ -69,7 +71,8 @@ EX <- function(...)
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     join_condition_matrix
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 }
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-#' @name evaluation
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+#' @name DF
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+#' @aliases DF
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 #' @rdname condition_eval_func
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 #' @export
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 DF <- function(...)
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@@ -1,4 +1,4 @@
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-#' GMQL Operation: COVER
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+#' Method cover
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 #'
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 #' It takes as input a dataset containing one or more samples and returns 
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 #' another dataset (with a single sample, if no \emph{groupby} option is 
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@@ -84,21 +84,21 @@
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 #' @param variation string identifying the cover GMQL function variation.
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 #' The admissible string are:
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 #' \itemize{
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-#' \item{flat: returns the contiguous region that starts from the first end 
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+#' \item{FLAT: returns the contiguous region that starts from the first end 
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 #' and stops at the last end of the regions which would contribute 
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 #' to each region of the \emph{cover}.}
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-#' \item{summit: returns regions that start from a position
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+#' \item{SUMMIT: returns regions that start from a position
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 #' where the number of intersecting regions is not increasing afterwards and
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 #' stops at a position where either the number of intersecting regions 
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 #' decreases, or it violates the max accumulation index.}
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-#' \item{histogram: returns the non-overlapping regions contributing to 
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+#' \item{HISTOGRAM: returns the non-overlapping regions contributing to 
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 #' the cover, each with its accumulation index value, which is assigned to 
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 #' the AccIndex region attribute.}
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-#' \item{cover: default value.}
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+#' \item{COVER: default value.}
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 #' }
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 #' 
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-#' @return GMQLDataset class object. It contains the value to use as input 
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-#' for the subsequent GMQL function
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+#' @return GMQLDataset object. It contains the value to use as input 
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+#' for the subsequent GMQLDataset method
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 #' 
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 #' @examples
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 #' 
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@@ -1,11 +1,11 @@
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 #' Method setdiff
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 #' 
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-#' Wrapper to GMQL difference function
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+#' @description Wrapper to GMQL difference function
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 #' 
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-#' It produces one sample in the result for each sample of the left operand,
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-#' by keeping the same metadata of the left input sample and only those 
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-#' regions (with their schema and values) of the left input sample which 
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-#' do not intersect with any region in the right operand sample.
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+#' @description It produces one sample in the result for each sample of the 
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+#' left operand, by keeping the same metadata of the left input sample 
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+#' and only those regions (with their schema and values) of the left input 
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+#' sample which do not intersect with any region in the right operand sample.
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 #' The optional \emph{joinby} clause is used to extract a subset of couples
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 #' from the cartesian product of two dataset \emph{x} and \emph{y} 
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 #' on which to apply the DIFFERENCE operator:
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@@ -38,8 +38,8 @@
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 #' left_input_data that overlap with at least one region in right_input_data 
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 #' (even just one base).
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 #' 
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-#' @return GMQLDataset class object. It contains the value to use as input 
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-#' for the subsequent GMQL function
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+#' @return GMQLDataset object. It contains the value to use as input 
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+#' for the subsequent GMQLDataset method
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 #' 
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 #'
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 #' @examples
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@@ -1,8 +1,8 @@
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-#' GMQL Operation: EXTEND
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+#' Method extend
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 #'
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-#' It generates new metadata attributes as result of aggregate functions 
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-#' applied to sample region attributes and adds them to the existing metadata 
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-#' attributes of the sample.
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+#' For each sample in an input dataset, it generates new metadata attributes 
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+#' as result of aggregate functions applied to sample region attributes 
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+#' and adds them to the existing metadata attributes of the sample.
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 #' Aggregate functions are applied sample by sample.
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 #'
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 #' @importFrom rJava .jnull
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@@ -11,8 +11,7 @@
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 #'
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 #' @param .data GMQLDataset class object 
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 #' @param ... Additional arguments for use in specific methods.
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-#' 
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-#' This method accept a series of aggregate function on region attribute.
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+#' It accept a series of aggregate function on region attribute.
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 #' All the element in the form \emph{key} = \emph{aggregate}.
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 #' The \emph{aggregate} is an object of class AGGREGATES
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 #' The aggregate functions available are: \code{\link{SUM}}, 
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@@ -30,8 +29,8 @@
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 #' }
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 #' "mixed style" is not allowed
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 #'
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-#' @return GMQLDataset class object. It contains the value to use as input 
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-#' for the subsequent GMQL function
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+#' @return GMQLDataset object. It contains the value to use as input 
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+#' for the subsequent GMQLDataset method
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 #' 
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 #' @examples
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 #'
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@@ -1,6 +1,4 @@
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 #' Method merge
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-#' 
3
-#' Wrapper to GMQL join function
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 #'
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 #' It takes in input two datasets, respectively known as nchor (left) 
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 #' and experiment (right) and returns a dataset of samples consisting of 
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@@ -57,8 +55,8 @@
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 #' the genometric predicate)}
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 #' }
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 #'
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-#' @return GMQLDataset class object. It contains the value to use as input 
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-#' for the subsequent GMQL function
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+#' @return GMQLDataset object. It contains the value to use as input 
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+#' for the subsequent GMQLDataset method
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 #' 
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 #' @examples
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 #' 
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@@ -1,4 +1,4 @@
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-#' GMQL Operation: MAP
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+#' Method map
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 #'
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 #' It computes, for each sample in the right dataset, aggregates over the 
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 #' values of the right regions that intersect with a region in a left sample, 
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@@ -52,8 +52,8 @@
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 #' if both end with value.}
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 #' }
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 #' 
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-#' @return GMQLDataset class object. It contains the value to use as input 
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-#' for the subsequent GMQL function
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+#' @return GMQLDataset object. It contains the value to use as input 
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+#' for the subsequent GMQLDataset method
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 #' 
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 #' @examples
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 #'
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@@ -1,7 +1,7 @@
1 1
 #' GMQL Function: EXECUTE
2 2
 #'
3 3
 #' Execute GMQL query.
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-#' The function works only after invoking at least one materialize
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+#' The function works only after invoking at least one collect
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 #' 
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 #' @importFrom rJava J
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 #' 
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@@ -67,7 +67,9 @@ execute <- function()
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68 68
 
69 69
 
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-#' GMQL Operation: MATERIALIZE
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+#' Method collect
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+#' 
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+#' Wrapper to GMQL materialize function
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 #'
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 #' It saves the contents of a dataset that contains samples metadata and 
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 #' samples regions.
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@@ -124,12 +126,12 @@ gmql_materialize <- function(input_data, dir_out, name)
124 126
 }
125 127
 
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-#' GMQL Operation: TAKE
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+#' Method take
128 130
 #'
129 131
 #' It saves the contents of a dataset that contains samples metadata 
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-#' and samples regions.
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-#' It is normally used to store in memoery the contents of any dataset 
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-#' generated during a GMQL query. the operation can be very time-consuming.
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+#' and samples regions as GrangesList.
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+#' It is normally used to store in memory the contents of any dataset 
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+#' generated during a GMQL query. The operation can be very time-consuming.
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 #' If you have invoked any materialization before take function, 
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 #' all those dataset will be materialized as folder.
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 #'
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@@ -1,13 +1,14 @@
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-#' GMQL Operation: MERGE
2
-#'
1
+#' Method aggregate
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+#' 
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 #' It builds a dataset consisting of a single sample having as many regions as
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 #' the number of regions of the input data and as many metadata as the union of
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-#' the 'attribute-value' tuples of the input samples. A groupby clause can be
6
-#' specified on metadata: the samples are then partitioned in groups, each with
7
-#' a distinct value of the grouping metadata attributes. The operation is
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-#' separately applied to each group, yielding one sample in the result for each
9
-#' group. Samples whose names are not present in the grouping metadata
10
-#' parameter are disregarded.
5
+#' the 'attribute-value' tuples of the input samples. 
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+#' If at least one evaluation function is specified: the samples are then 
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+#' partitioned in groups, each with a distinct value of the grouping metadata 
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+#' attributes. The operation is separately applied to each group, yielding 
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+#' one sample in the result for each group. 
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+#' Samples whose names are not present in the grouping metadata parameter 
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+#' are disregarded.
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 #'
12 13
 #' @importFrom rJava J
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 #' @importFrom rJava .jnull
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@@ -15,8 +16,7 @@
15 16
 #'
16 17
 #' @param x GMQLDataset class object
17 18
 #' @param ... Additional arguments for use in specific methods.
18
-#'
19
-#' list of evalation function to define condition evaluation on metadata:
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+#' It accepts a list of evalation function to define evaluation on metadata:
20 20
 #' \itemize{
21 21
 #' \item{\code{\link{FN}}: Fullname evaluation, two attributes match 
22 22
 #' if they both end with value and, if they have a further prefixes,
... ...
@@ -27,8 +27,8 @@
27 27
 #' if both end with value.}
28 28
 #' }
29 29
 #' 
30
-#' @return DataSet class object. It contains the value to use as input for the
31
-#'   subsequent GMQL function
30
+#' @return GMQLDataset object. It contains the value to use as input 
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+#' for the subsequent GMQLDataset method
32 32
 #'
33 33
 #' @examples
34 34
 #'
... ...
@@ -1,28 +1,22 @@
1
-#' GMQL operation: ORDER
1
+#' Method arrange
2 2
 #'
3 3
 #' It is used to order either samples or sample regions or both, according to 
4 4
 #' a set of metadata and/or region attributes, and/or region coordinates.
5 5
 #' Order can be specified as ascending / descending for every attribute
6 6
 #' The number of samples and their regions remain the same 
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-#' (unless mtop/rtop parameters specified) but a new ordering metadata 
7
+#' (unless fetching options are specified) but a new ordering metadata 
8 8
 #' and/or region attribute is added.
9 9
 #' Sorted samples or regions have a new attribute "order", 
10
-#' added to either metadata, or regions, or both of them as specified in input
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-#' The input mtop = k and rtop = m extracts the first k samples 
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-#' and m regions respectively, the clause mtopg = k and rtopg = m 
13
-#' performs grouping operation, grouping by identical values 
14
-#' of ordering attributes and then selects the first k samples 
15
-#' or regions of each group
10
+#' added to either metadata, or regions, or both of them as specified in inputs
16 11
 #'
17 12
 #' @importFrom rJava J
18 13
 #' @importFrom rJava .jnull
19 14
 #' @importFrom rJava .jarray
20 15
 #' 
21 16
 #' @param .data GMQLDataset class object
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-#' @param metadata_ordering list of order objects where every object 
23
-#' contains the name of metadata.
24
-#' The ORDER's available are: \code{\link{ASC}}, \code{\link{DESC}}
25
-#' Every condition accepts only one string value. (e.g. ASC("cell_type") )
17
+#' @param metadata_ordering list of ordering function contains name of 
18
+#' metadata.
19
+#' The function available are: \code{\link{ASC}}, \code{\link{DESC}}
26 20
 #' 
27 21
 #' @param fetch_opt string indicating the option used to fetch the 
28 22
 #' first k sample:
... ...
@@ -36,10 +30,9 @@
36 30
 #' @param num_fetch integer value identifying the number of region to fetch
37 31
 #' by default is 0, that's means all sample are fetched
38 32
 #' s
39
-#' @param regions_ordering list of ORDER objects where every object contains 
40
-#' the name of region schema value.
41
-#' The ORDER's available are: \code{\link{ASC}}, \code{\link{DESC}}.
42
-#' Every condition accepts only one string value. (e.g. DESC("pvalue") )
33
+#' @param regions_ordering list of ordering function contains 
34
+#' name of region schema value.
35
+#' The function available are: \code{\link{ASC}}, \code{\link{DESC}}.
43 36
 #' 
44 37
 #' @param reg_fetch_opt string indicating the option used to fetch the 
45 38
 #' first k regions:
... ...
@@ -54,10 +47,8 @@
54 47
 #' by default is 0, that's means all regions are fetched
55 48
 #' @param ... Additional arguments for use in specific methods.
56 49
 #' 
57
-#' 
58
-#' @return DataSet class object. It contains the value to use as input 
59
-#' for the subsequent GMQL function
60
-#' 
50
+#' @return GMQLDataset object. It contains the value to use as input 
51
+#' for the subsequent GMQLDataset method
61 52
 #'
62 53
 #' @examples
63 54
 #' 
... ...
@@ -1,16 +1,15 @@
1
-#' GMQL Operation: PROJECT
1
+#' Method select
2 2
 #'
3 3
 #' It creates, from an existing dataset, a new dataset with all the samples 
4 4
 #' from input dataset, but keeping for each sample in the input dataset 
5
-#' only those metadata and/or region attributes expressed in the operator 
6
-#' parameter list.
5
+#' only those metadata and/or region attributes expressed.
7 6
 #' Region coordinates and values of the remaining metadata remain equal to 
8 7
 #' those in the input dataset. It allows to:
9 8
 #' \itemize{
10 9
 #' \item{Remove existing metadata and/or region attributes from a dataset}
11
-#' \item{Create new metadata and/or region attributes in the result}
10
+#' \item{Update new metadata and/or region attributes in the result}
12 11
 #' }
13
-#'
12
+#' 
14 13
 #' @importFrom rJava J
15 14
 #' @importFrom rJava .jnull
16 15
 #' @importFrom rJava .jarray
... ...
@@ -48,8 +47,8 @@
48 47
 #' 
49 48
 #' @param ... Additional arguments for use in specific methods.
50 49
 #' 
51
-#' @return GMQLDataset class object. It contains the value to use as input 
52
-#' for the subsequent GMQL function
50
+#' @return GMQLDataset object. It contains the value to use as input 
51
+#' for the subsequent GMQLDataset method
53 52
 #'
54 53
 #' @examples
55 54
 #' 
... ...
@@ -94,7 +93,7 @@
94 93
 setMethod("select", "GMQLDataset",
95 94
             function(.data, metadata = NULL, metadata_update = NULL, 
96 95
                         all_but_meta = FALSE, regions = NULL, 
97
-                        regions_update = NULL, all_but_reg=FALSE)
96
+                        regions_update = NULL, all_but_reg = FALSE, ...)
98 97
             {
99 98
                 data = .data@value
100 99
                 r_update <- substitute(regions_update)
... ...
@@ -22,7 +22,7 @@
22 22
 #' You can always perform it, calling the function \code{\link{login_gmql}} 
23 23
 #' explicitly
24 24
 #' 
25
-#' @param username string name used during signup
25
+#' @param username string name used during signup 
26 26
 #' @param password string password used during signup
27 27
 #' 
28 28
 #' @return None
... ...
@@ -62,10 +62,10 @@ init_gmql <- function(output_format = "gtf", remote_processing = FALSE,
62 62
     WrappeR$initGMQL(out_format,remote_processing)
63 63
 }
64 64
 
65
-#' GMQL Function: READ
65
+#' Function read
66 66
 #'
67
-#' Read a GMQL dataset or any other folder containig some homogenus sample
68
-#' from disk, saving in Scala memory that can be referenced in R
67
+#' Read a GMQL dataset, folder containig some homogenus sample from disk 
68
+#' or GrangesList saving in Scala memory that can be referenced in R.
69 69
 #' Also used to read a repository dataset in case of remote processing.
70 70
 #' 
71 71
 #' @importFrom rJava .jnull
... ...
@@ -89,8 +89,8 @@ init_gmql <- function(output_format = "gtf", remote_processing = FALSE,
89 89
 #' @param is_local logical value indicating local or remote dataset
90 90
 #' @param is_GMQL logical value indicating if is a GMQL dataset or not 
91 91
 #' 
92
-#' @return DataSet class object. It contains the value to use as input 
93
-#' for the subsequent GMQL function
92
+#' @return GMQLDataset object. It contains the value to use as input 
93
+#' for the subsequent GMQLDataset method
94 94
 #' 
95 95
 #' @details
96 96
 #' Normally a GMQL dataset contains an XML schema file that contains
... ...
@@ -98,6 +98,13 @@ init_gmql <- function(output_format = "gtf", remote_processing = FALSE,
98 98
 #' The CustomParser read this XML schema; 
99 99
 #' if you already know what kind of schema your files are, use one of the 
100 100
 #' parser defined without reading any XML schema
101
+#' 
102
+#' If GrangesList has no metadata: i.e. metadata() is empty, two metadata are
103
+#' generated.
104
+#' \itemize{
105
+#' \item{"Provider" = "Polimi"}
106
+#' \item{"Application" = "RGMQL"}
107
+#' }
101 108
 #'
102 109
 #' @examples
103 110
 #' 
... ...
@@ -114,7 +121,7 @@ init_gmql <- function(output_format = "gtf", remote_processing = FALSE,
114 121
 #' r = read_dataset(test_path,"ANNParser")
115 122
 #' 
116 123
 #' ## read remote public dataset stored into GMQL system repository 
117
-#' 
124
+#' ## If public dataset a prefix "public." is needed before dataset name
118 125
 #' r2 = read_dataset("public.HG19_TCGA_dnaseq",is_local = FALSE)
119 126
 #' 
120 127
 #' }
... ...
@@ -179,17 +186,13 @@ read_dataset <- function(dataset, parser = "CustomParser", is_local=TRUE,
179 186
         GMQLDataset(data)
180 187
 }
181 188
 
182
-#' GMQL Function: READ
183
-#'
184
-#' Read a GrangesList saving in scala memory that can be referenced in R
185
-#'
189
+
186 190
 #' @importFrom S4Vectors metadata
187 191
 #' @importFrom rJava J
188 192
 #' @importFrom rJava .jarray
189 193
 #' 
190 194
 #' @param samples GrangesList
191 195
 #' 
192
-#' 
193 196
 #' @name read
194 197
 #' @rdname read-function
195 198
 #' @export
... ...
@@ -274,11 +277,11 @@ We provide two metadata for you")
274 277
 
275 278
 #' Disable or Enable remote processing
276 279
 #'
277
-#' It allows to enable or disable remote processing
280
+#' It allows to enable or disable remote processing 
278 281
 #' 
279 282
 #' @details 
280 283
 #' The invocation of this function allow to change mode of processing.
281
-#' after materialization is not possbile to switch the processing mode, 
284
+#' after invoking collect() is not possbile to switch the processing mode, 
282 285
 #' 
283 286
 #' @importFrom rJava J
284 287
 #' 
... ...
@@ -290,7 +293,7 @@ We provide two metadata for you")
290 293
 #' @examples
291 294
 #' 
292 295
 #' # initialize with remote processing off
293
-#' init_gmql("tab",remote_processing=FALSE)
296
+#' init_gmql("tab",remote_processing = FALSE)
294 297
 #' 
295 298
 #' # change processing mode to remote
296 299
 #' remote_processing(TRUE)
... ...
@@ -1,13 +1,13 @@
1
-#' GMQL Operation: SELECT
2
-#'
3
-#' It returns all the samples satisfying the predicate on metadata.
4
-#' If regions are specified, returns regions satisfying the predicate 
5
-#' on regions.
6
-#' If semijoin clauses are specified they are applied, too.
7
-#' When semijoin is defined, it extracts those samples containing all metadata 
8
-#' attribute defined in semijoin clause with at least one metadata value 
9
-#' in common with semi join dataset.
10
-#' If no metadata in common between input dataset and semi join dataset, 
1
+#' Method filter
2
+#' 
3
+#' It creates a new dataset from an existing one by extracting a subset of 
4
+#' samples and/or regions from the input dataset according to their predicate.
5
+#' each sample in the output dataset has the same region attributes, 
6
+#' values, and metadata as in the input dataset.
7
+#' When semijoin function is defined, it extracts those samples containing 
8
+#' all metadata attribute defined in semijoin clause with at least 
9
+#' one metadata value in common with semijoin dataset.
10
+#' If no metadata in common between input dataset and semijoin dataset, 
11 11
 #' no sample is extracted.
12 12
 #'
13 13
 #' @importFrom rJava J
... ...
@@ -20,16 +20,15 @@
20 20
 #' on metadata attribute. 
21 21
 #' Only !, |, ||, &, && are admitted.
22 22
 #' @param r_predicate logical predicate made up by R logical operation 
23
-#' on chema region values. 
23
+#' on schema region values. 
24 24
 #' Only !, |, ||, &, && are admitted.
25 25
 #' @param ... Additional arguments for use in specific methods.
26
-#' 
27
-#' @param semijoin \code{\link{semijoin}} function 
26
+#' It is also accept \code{\link{semijoin}} function 
28 27
 #' to define filter method with semijoin condition (see examples).
29 28
 #' 
30 29
 #' 
31
-#' @return GMQLDataset class object. It contains the value to use as input 
32
-#' for the subsequent GMQL function
30
+#' @return GMQLDataset object. It contains the value to use as input 
31
+#' for the subsequent GMQLDataset method
33 32
 #' 
34 33
 #' @examples
35 34
 #' 
... ...
@@ -43,17 +42,17 @@
43 42
 #' 
44 43
 #' \dontrun{
45 44
 #' 
46
-#' It creates a new dataset called 'jun_tf' by selecting those samples and 
47
-#' their regions from the existing 'data' dataset such that:
48
-#' Each output sample has a metadata attribute called antibody_target 
49
-#' with value JUN.
50
-#' Each output sample also has not a metadata attribute called "cell" 
51
-#' that has the same value of at least one of the values that a metadata 
52
-#' attribute equally called cell has in at least one sample 
53
-#' of the 'join_data' dataset.
54
-#' For each sample satisfying previous condition,only its regions that 
55
-#' have a region attribute called pValue with the associated value 
56
-#' less than 0.01 are conserved in output
45
+#' # It creates a new dataset called 'jun_tf' by selecting those samples and 
46
+#' # their regions from the existing 'data' dataset such that:
47
+#' # Each output sample has a metadata attribute called antibody_target 
48
+#' # with value JUN.
49
+#' # Each output sample also has not a metadata attribute called "cell" 
50
+#' # that has the same value of at least one of the values that a metadata 
51
+#' # attribute equally called cell has in at least one sample 
52
+#' # of the 'join_data' dataset.
53
+#' # For each sample satisfying previous condition,only its regions that 
54
+#' # have a region attribute called pValue with the associated value 
55
+#' # less than 0.01 are conserved in output
57 56
 #' 
58 57
 #' 
59 58
 #' init_gmql()
... ...
@@ -131,8 +130,7 @@ gmql_select <- function(input_data, predicate, region_predicate, s_join)
131 130
 #' considering semi_join IN semi_join_dataset
132 131
 #' 
133 132
 #' @param ... Additional arguments for use in specific methods.
134
-#' 
135
-#' This method accept a function to define condition evaluation on metadata.
133
+#' It is also accpet a functions to define condition evaluation on metadata.
136 134
 #' \itemize{
137 135
 #' \item{\code{\link{FN}}: Fullname evaluation, two attributes match 
138 136
 #' if they both end with value and, if they have a further prefixes,
... ...
@@ -143,9 +141,30 @@ gmql_select <- function(input_data, predicate, region_predicate, s_join)
143 141
 #' if both end with value.}
144 142
 #' }
145 143
 #' 
144
+#' @examples
145
+#' 
146
+#' # It creates a new dataset called 'jun_tf' by selecting those samples and 
147
+#' # their regions from the existing 'data' dataset such that:
148
+#' # Each output sample has a metadata attribute called antibody_target 
149
+#' # with value JUN.
150
+#' # Each output sample also has not a metadata attribute called "cell" 
151
+#' # that has the same value of at least one of the values that a metadata 
152
+#' # attribute equally called cell has in at least one sample 
153
+#' # of the 'join_data' dataset.
154
+#' # For each sample satisfying previous condition,only its regions that 
155
+#' # have a region attribute called pValue with the associated value 
156
+#' # less than 0.01 are conserved in output
157
+#' 
158
+#' 
159
+#' init_gmql()
160
+#' test_path <- system.file("example", "DATASET", package = "RGMQL")
161
+#' test_path2 <- system.file("example", "DATASET_GDM", package = "RGMQL")
162
+#' data <- read_dataset(test_path)
163
+#' join_data <-  read_dataset(test_path2)
164
+#' jun_tf <- filter(data,NULL,NULL, semijoin(join_data, TRUE, DF("cell")))
165
+#' 
146 166
 #' @return semijoin condition as list
147 167
 #' @export
148
-#' 
149 168
 semijoin <- function(data, not_in = FALSE, ...)
150 169
 {
151 170
     semij_cond = list(...)
... ...
@@ -1,10 +1,10 @@
1 1
 #' Method union
2 2
 #' 
3
-#' Wrapper to GMQL union function
3
+#' @description Wrapper to GMQL union function
4 4
 #' 
5
-#' It is used to integrate homogeneous or heterogeneous samples of two datasets 
6
-#' within a single dataset; for each sample of either input dataset, 
7
-#' a result sample is created as follows:
5
+#' @description It is used to integrate homogeneous or heterogeneous samples 
6
+#' of two datasets within a single dataset; for each sample of either input 
7
+#' dataset, a result sample is created as follows:
8 8
 #' \itemize{
9 9
 #' \item {Metadata are the same as in the original sample.}
10 10
 #' \item {Resulting schema is obtained by projecting the schema 
... ...
@@ -23,11 +23,11 @@
23 23
 #' 
24 24
 #' @importFrom rJava J
25 25
 #' 
26
-#' @param x GMQLDataset class object
27
-#' @param y GMQLDataset class object 
26
+#' @param x GMQLDataset object
27
+#' @param y GMQLDataset object 
28 28
 #'
29
-#' @return GMQLDataset class object. It contains the value to use as input 
30
-#' for the subsequent GMQL function
29
+#' @return GMQLDataset object. It contains the value to use as input 
30
+#' for the subsequent GMQLDataset method
31 31
 #'
32 32
 #' @examples
33 33
 #' 
... ...
@@ -6,14 +6,15 @@
6 6
 #' Ordering functions
7 7
 #'
8 8
 #' These functions is used to create a series of metadata as string
9
-#' that require ordering on value.
9
+#' that require ordering on value; is used only in arrange method.
10
+#' (see example)
10 11
 #' 
11 12
 #' \itemize{
12 13
 #' \item{ASC: It defines a ascending order for input value}
13 14
 #' \item{DESC: It defines a descending order for input value}
14 15
 #' }
15 16
 #' 
16
-#' @param ... Additional arguments for use in specific methods.
17
+#' @param ... series of metatdata as string
17 18
 #'
18 19
 #' @return ordering object
19 20
 #' 
... ...
@@ -33,7 +34,8 @@
33 34
 #' fetch_opt = "mtop", num_fetch = 5, reg_fetch_opt = "rtop", 
34 35
 #' reg_num_fetch = 7)
35 36
 #' 
36
-#' @name ORDERING
37
+#' @name DESC
38
+#' @aliases DESC
37 39
 #' @rdname ordering-class
38 40
 #' @export
39 41
 #'
... ...
@@ -54,7 +56,8 @@ DESC <- function(...)
54 56
     order_matrix
55 57
 }
56 58
 
57
-#' @name ORDERING
59
+#' @name ASC
60
+#' @aliases ASC
58 61
 #' @rdname ordering-class
59 62
 #' @export
60 63
 #'
... ...
@@ -24,15 +24,13 @@ if(getRversion() >= "3.1.0")
24 24
 #' @param username string name used during signup
25 25
 #' @param password string password used during signup
26 26
 #'
27
-#' @seealso \code{\link{logout_gmql}}
28
-#'
29 27
 #' @details
30 28
 #' if both username and password are NULL you will be logged as guest
31 29
 #' After login you will receive an authentication token.
32 30
 #' As token remains vaild on server (until the next login / registration) 
33 31
 #' a user can safely use a token fora previous session as a convenience, 
34 32
 #' this token is saved in Global environment to perform subsequent REST call 
35
-#' even on complete R restart (if is environemnt has been saved, of course ...)
33
+#' even on complete R restart (if is environemnt has been saved)
36 34
 #' If error occures a specific error is printed
37 35
 #'
38 36
 #' @return None
... ...
@@ -149,8 +147,8 @@ logout_gmql <- function(url)
149 147
 
150 148
 #' Shows all Queries
151 149
 #'
152
-#' It shows all the GMQL query saved on repository 
153
-#' using the proper GMQL web service available on a remote server
150
+#' It shows all the GMQL query saved on repository using the proper GMQL 
151
+#' web service available on a remote server
154 152
 #' 
155 153
 #' @import httr
156 154
 #'
... ...
@@ -168,6 +166,7 @@ logout_gmql <- function(url)
168 166
 #' if error occures, a specific error is printed
169 167
 #'
170 168
 #' @examples 
169
+#' 
171 170
 #' remote_url = "http://genomic.elet.polimi.it/gmql-rest-r"
172 171
 #' login_gmql(remote_url)
173 172
 #' list <- show_queries_list(remote_url)
... ...
@@ -460,12 +459,14 @@ stop_job <- function(url, job_id)
460 459
 #' If error occures a specific error is printed
461 460
 #'
462 461
 #' @examples
463
-#' \dontrun{
462
+#' 
464 463
 #' remote_url = "http://genomic.elet.polimi.it/gmql-rest-r"
465 464
 #' login_gmql(remote_url)
466 465
 #' 
467 466
 #' ## list all jobs
468 467
 #' list_jobs <- show_jobs_list(remote_url)
468
+#' 
469
+#' \dontrun{
469 470
 #' jobs_1 <- list_jobs$jobs[[1]]
470 471
 #' 
471 472
 #' ## show job log
... ...
@@ -518,7 +519,9 @@ trace_job <- function(url, job_id)
518 519
 
519 520
 #' Show all jobs
520 521
 #'
521
-#' It show all Jobs (run, succeded or failed) invoked by user
522
+#' It show all Jobs (run, succeded or failed) invoked by user using the proper 
523
+#' GMQL web service available on a remote server
524
+#' 
522 525
 #' @import httr
523 526
 #' @param url string url of server: It must contain the server address 
524 527
 #' and base url; service name is added automatically
... ...
@@ -832,9 +835,7 @@ upload_dataset <- function(url,datasetName,folderPath,schemaName=NULL,
832 835
 #' @details
833 836
 #' If no error occur, print "Deleted Dataset", otherwise a specific error 
834 837
 #' is printed
835
-#'
836
-#' @seealso \code{\link{download_dataset}}
837
-#'
838
+#' 
838 839
 #' @examples
839 840
 #'
840 841
 #' \dontrun{
... ...
@@ -885,7 +886,6 @@ delete_dataset <- function(url,datasetName)
885 886
 #' @details
886 887
 #' If error occures a specific error is printed
887 888
 #'
888
-#'
889 889
 #' @examples
890 890
 #'
891 891
 #' ## download dataset in r working directory
892 892
Binary files a/inst/java/GMQL.jar and b/inst/java/GMQL.jar differ
... ...
@@ -16,6 +16,8 @@ instance of GMQL dataset
16 16
 }
17 17
 \description{
18 18
 Abstract class representing GMQL dataset
19
+
20
+Alloc GMQLDataset object with its value
19 21
 }
20 22
 \section{Slots}{
21 23
 
... ...
@@ -1,29 +1,17 @@
1 1
 % Generated by roxygen2: do not edit by hand
2 2
 % Please edit documentation in R/S3Aggregates.R
3
-\name{AGGREGATES}
4
-\alias{AGGREGATES}
3
+\name{SUM}
5 4
 \alias{SUM}
6
-\alias{AGGREGATES}
7 5
 \alias{MIN}
8
-\alias{AGGREGATES}
9 6
 \alias{MAX}
10
-\alias{AGGREGATES}
11 7
 \alias{AVG}
12
-\alias{AGGREGATES}
13 8
 \alias{BAG}
14
-\alias{AGGREGATES}
15 9
 \alias{COUNT}
16
-\alias{AGGREGATES}
17 10
 \alias{STD}
18
-\alias{AGGREGATES}
19 11
 \alias{MEDIAN}
20
-\alias{AGGREGATES}
21 12
 \alias{Q1}
22
-\alias{AGGREGATES}
23 13
 \alias{Q2}
24
-\alias{AGGREGATES}
25 14
 \alias{Q3}
26
-\alias{AGGREGATES}
27 15
 \alias{BAGD}
28 16
 \title{AGGREGATES object class constructor}
29 17
 \usage{
... ...
@@ -15,8 +15,7 @@ aggregate(x, ...)
15 15
 \item{x}{GMQLDataset class object}
16 16
 
17 17
 \item{...}{Additional arguments for use in specific methods.
18
-
19
-list of evalation function to define condition evaluation on metadata:
18
+It accepts a list of evalation function to define evaluation on metadata:
20 19
 \itemize{
21 20
 \item{\code{\link{FN}}: Fullname evaluation, two attributes match 
22 21
 if they both end with value and, if they have a further prefixes,
... ...
@@ -28,20 +27,21 @@ if both end with value.}
28 27
 }}
29 28
 }
30 29
 \value{
31
-DataSet class object. It contains the value to use as input for the
32
-  subsequent GMQL function
30
+GMQLDataset object. It contains the value to use as input 
31
+for the subsequent GMQLDataset method
33 32
 }
34 33
 \description{
35 34
 Wrapper to GMQL merge function
36 35
 
37 36
 It builds a dataset consisting of a single sample having as many regions as
38 37
 the number of regions of the input data and as many metadata as the union of
39
-the 'attribute-value' tuples of the input samples. A groupby clause can be
40
-specified on metadata: the samples are then partitioned in groups, each with
41
-a distinct value of the grouping metadata attributes. The operation is
42
-separately applied to each group, yielding one sample in the result for each
43
-group. Samples whose names are not present in the grouping metadata
44
-parameter are disregarded.
38
+the 'attribute-value' tuples of the input samples. 
39
+If at least one evaluation function is specified: the samples are then 
40
+partitioned in groups, each with a distinct value of the grouping metadata 
41
+attributes. The operation is separately applied to each group, yielding 
42
+one sample in the result for each group. 
43
+Samples whose names are not present in the grouping metadata parameter 
44
+are disregarded.
45 45
 }
46 46
 \examples{
47 47
 
... ...
@@ -18,15 +18,13 @@ arrange(.data, metadata_ordering = NULL, regions_ordering = NULL,
18 18
 \arguments{
19 19
 \item{.data}{GMQLDataset class object}
20 20
 
21
-\item{metadata_ordering}{list of order objects where every object 
22
-contains the name of metadata.
23
-The ORDER's available are: \code{\link{ASC}}, \code{\link{DESC}}
24
-Every condition accepts only one string value. (e.g. ASC("cell_type") )}
21
+\item{metadata_ordering}{list of ordering function contains name of 
22
+metadata.
23
+The function available are: \code{\link{ASC}}, \code{\link{DESC}}}
25 24
 
26
-\item{regions_ordering}{list of ORDER objects where every object contains 
27
-the name of region schema value.
28
-The ORDER's available are: \code{\link{ASC}}, \code{\link{DESC}}.
29
-Every condition accepts only one string value. (e.g. DESC("pvalue") )}
25
+\item{regions_ordering}{list of ordering function contains 
26
+name of region schema value.
27
+The function available are: \code{\link{ASC}}, \code{\link{DESC}}.}
30 28
 
31 29
 \item{fetch_opt}{string indicating the option used to fetch the 
32 30
 first k sample:
... ...
@@ -56,8 +54,8 @@ by default is 0, that's means all regions are fetched}
56 54
 \item{...}{Additional arguments for use in specific methods.}
57 55
 }
58 56
 \value{
59
-DataSet class object. It contains the value to use as input 
60
-for the subsequent GMQL function
57
+GMQLDataset object. It contains the value to use as input 
58
+for the subsequent GMQLDataset method
61 59
 }
62 60
 \description{
63 61
 Wrapper to GMQL order function
... ...
@@ -66,15 +64,10 @@ It is used to order either samples or sample regions or both, according to
66 64
 a set of metadata and/or region attributes, and/or region coordinates.
67 65
 Order can be specified as ascending / descending for every attribute
68 66
 The number of samples and their regions remain the same 
69
-(unless mtop/rtop parameters specified) but a new ordering metadata 
67
+(unless fetching options are specified) but a new ordering metadata 
70 68
 and/or region attribute is added.
71 69
 Sorted samples or regions have a new attribute "order", 
72
-added to either metadata, or regions, or both of them as specified in input
73
-The input mtop = k and rtop = m extracts the first k samples 
74
-and m regions respectively, the clause mtopg = k and rtopg = m 
75
-performs grouping operation, grouping by identical values 
76
-of ordering attributes and then selects the first k samples 
77
-or regions of each group
70
+added to either metadata, or regions, or both of them as specified in inputs
78 71
 }
79 72
 \examples{
80 73
 
... ...
@@ -27,6 +27,9 @@ None
27 27
 \description{
28 28
 Wrapper to GMQL materialize function
29 29
 
30
+Wrapper to GMQL materialize function
31
+}
32
+\details{
30 33
 It saves the contents of a dataset that contains samples metadata and 
31 34
 samples regions.
32 35
 It is normally used to persist the contents of any dataset generated 
... ...
@@ -1,11 +1,8 @@
1 1
 % Generated by roxygen2: do not edit by hand
2 2
 % Please edit documentation in R/evaluation-functions.R
3
-\name{evaluation}
4
-\alias{evaluation}
3
+\name{FN}
5 4
 \alias{FN}
6
-\alias{evaluation}
7 5
 \alias{EX}
8
-\alias{evaluation}
9 6
 \alias{DF}
10 7
 \title{Condition evaluation functions}
11 8
 \usage{
... ...
@@ -74,22 +74,22 @@ if both end with value.}
74 74
 \item{variation}{string identifying the cover GMQL function variation.
75 75
 The admissible string are:
76 76
 \itemize{
77
-\item{flat: returns the contiguous region that starts from the first end 
77
+\item{FLAT: returns the contiguous region that starts from the first end 
78 78
 and stops at the last end of the regions which would contribute 
79 79
 to each region of the \emph{cover}.}
80
-\item{summit: returns regions that start from a position
80
+\item{SUMMIT: returns regions that start from a position
81 81
 where the number of intersecting regions is not increasing afterwards and
82 82
 stops at a position where either the number of intersecting regions 
83 83
 decreases, or it violates the max accumulation index.}
84
-\item{histogram: returns the non-overlapping regions contributing to 
84
+\item{HISTOGRAM: returns the non-overlapping regions contributing to 
85 85
 the cover, each with its accumulation index value, which is assigned to 
86 86
 the AccIndex region attribute.}
87
-\item{cover: default value.}
87
+\item{COVER: default value.}
88 88
 }}
89 89
 }
90 90
 \value{
91
-GMQLDataset class object. It contains the value to use as input 
92
-for the subsequent GMQL function
91
+GMQLDataset object. It contains the value to use as input 
92
+for the subsequent GMQLDataset method
93 93
 }
94 94
 \description{
95 95
 Wrapper to GMQL cover function
... ...
@@ -1,9 +1,7 @@
1 1
 % Generated by roxygen2: do not edit by hand
2 2
 % Please edit documentation in R/S3Cover-Param.R
3
-\name{COVER-PARAMETER}
4
-\alias{COVER-PARAMETER}
3
+\name{ALL}
5 4
 \alias{ALL}
6
-\alias{COVER-PARAMETER}
7 5
 \alias{ANY}
8 6
 \title{PARAM object class constructor}
9 7
 \usage{
... ...
@@ -36,6 +36,3 @@ delete_dataset(remote_url, "job_test1_test101_20170604_180908_RESULT_DS")
36 36
 }
37 37
 
38 38
 }
39
-\seealso{
40
-\code{\link{download_dataset}}
41
-}
... ...
@@ -1,19 +1,12 @@
1 1
 % Generated by roxygen2: do not edit by hand
2 2
 % Please edit documentation in R/S3Distal.R
3
-\name{DISTAL}
4
-\alias{DISTAL}
3
+\name{DL}
5 4
 \alias{DL}
6
-\alias{DISTAL}
7 5
 \alias{DG}
8
-\alias{DISTAL}
9 6
 \alias{DLE}
10
-\alias{DISTAL}
11 7
 \alias{DGE}
12
-\alias{DISTAL}
13 8
 \alias{MD}
14
-\alias{DISTAL}
15 9
 \alias{UP}
16
-\alias{DISTAL}
17 10
 \alias{DOWN}
18 11
 \title{DISTAL object class constructor}
19 12
 \usage{
... ...
@@ -11,7 +11,7 @@ None
11 11
 }
12 12
 \description{
13 13
 Execute GMQL query.
14
-The function works only after invoking at least one materialize
14
+The function works only after invoking at least one collect
15 15
 }
16 16
 \examples{
17 17
 
... ...
@@ -36,7 +36,6 @@ its metadata file
36 36
 }
37 37
 \examples{
38 38
 
39
-\dontrun{
40 39
 library(GenomicRanges)
41 40
 gr1 <- GRanges(seqnames = "chr2", ranges = IRanges(3, 6), strand = "+", 
42 41
 score = 5L, GC = 0.45)
... ...
@@ -46,7 +45,8 @@ score = 3:4, GC = c(0.3, 0.5))
46 45
 grl = GRangesList(gr1, gr2)
47 46
 test_out_path <- system.file("example", package = "RGMQL")
48 47
 export_gmql(grl, test_out_path,TRUE)
49
-}
48
+
49
+
50 50
 }
51 51
 \seealso{
52 52
 \code{\link{import_gmql}}
... ...
@@ -16,8 +16,7 @@ extend(.data, ...)
16 16
 \item{.data}{GMQLDataset class object}
17 17
 
18 18
 \item{...}{Additional arguments for use in specific methods.
19
-
20
-This method accept a series of aggregate function on region attribute.
19
+It accept a series of aggregate function on region attribute.
21 20
 All the element in the form \emph{key} = \emph{aggregate}.
22 21
 The \emph{aggregate} is an object of class AGGREGATES
23 22
 The aggregate functions available are: \code{\link{SUM}}, 
... ...
@@ -36,15 +35,15 @@ attributes. Two style are allowed:
36 35
 "mixed style" is not allowed}
37 36
 }
38 37
 \value{
39
-GMQLDataset class object. It contains the value to use as input 
40
-for the subsequent GMQL function
38
+GMQLDataset object. It contains the value to use as input 
39
+for the subsequent GMQLDataset method
41 40
 }
42 41
 \description{
43 42
 Wrapper to GMQL extend function
44 43
 
45
-It generates new metadata attributes as result of aggregate functions 
46
-applied to sample region attributes and adds them to the existing metadata 
47
-attributes of the sample.
44
+For each sample in an input dataset, it generates new metadata attributes 
45
+as result of aggregate functions applied to sample region attributes 
46
+and adds them to the existing metadata attributes of the sample.
48 47
 Aggregate functions are applied sample by sample.
49 48
 }
50 49
 \examples{
... ...
@@ -22,29 +22,28 @@ on metadata attribute.
22 22
 Only !, |, ||, &, && are admitted.}
23 23
 
24 24
 \item{r_predicate}{logical predicate made up by R logical operation 
25
-on chema region values. 
25
+on schema region values. 
26 26
 Only !, |, ||, &, && are admitted.}
27 27
 
28
-\item{semijoin}{\code{\link{semijoin}} function 
28
+\item{...}{Additional arguments for use in specific methods.
29
+It is also accept \code{\link{semijoin}} function 
29 30
 to define filter method with semijoin condition (see examples).}
30
-
31
-\item{...}{Additional arguments for use in specific methods.}
32 31
 }
33 32
 \value{
34
-GMQLDataset class object. It contains the value to use as input 
35
-for the subsequent GMQL function
33
+GMQLDataset object. It contains the value to use as input 
34
+for the subsequent GMQLDataset method
36 35
 }
37 36
 \description{
38 37
 Wrapper to GMQL select function
39 38
 
40
-It returns all the samples satisfying the predicate on metadata.
41
-If regions are specified, returns regions satisfying the predicate 
42
-on regions.
43
-If semijoin clauses are specified they are applied, too.
44
-When semijoin is defined, it extracts those samples containing all metadata 
45
-attribute defined in semijoin clause with at least one metadata value 
46
-in common with semi join dataset.
47
-If no metadata in common between input dataset and semi join dataset, 
39
+It creates a new dataset from an existing one by extracting a subset of 
40
+samples and/or regions from the input dataset according to their predicate.
41
+each sample in the output dataset has the same region attributes, 
42
+values, and metadata as in the input dataset.
43
+When semijoin function is defined, it extracts those samples containing 
44
+all metadata attribute defined in semijoin clause with at least 
45
+one metadata value in common with semijoin dataset.
46
+If no metadata in common between input dataset and semijoin dataset, 
48 47
 no sample is extracted.
49 48
 }
50 49
 \examples{
... ...
@@ -59,17 +58,17 @@ s <- filter(input, Patient_age < 70)
59 58
 
60 59
 \dontrun{
61 60
 
62
-It creates a new dataset called 'jun_tf' by selecting those samples and 
63
-their regions from the existing 'data' dataset such that:
64
-Each output sample has a metadata attribute called antibody_target 
65
-with value JUN.
66
-Each output sample also has not a metadata attribute called "cell" 
67
-that has the same value of at least one of the values that a metadata 
68
-attribute equally called cell has in at least one sample 
69
-of the 'join_data' dataset.
70
-For each sample satisfying previous condition,only its regions that 
71
-have a region attribute called pValue with the associated value 
72
-less than 0.01 are conserved in output
61
+# It creates a new dataset called 'jun_tf' by selecting those samples and 
62
+# their regions from the existing 'data' dataset such that:
63
+# Each output sample has a metadata attribute called antibody_target 
64
+# with value JUN.
65
+# Each output sample also has not a metadata attribute called "cell" 
66
+# that has the same value of at least one of the values that a metadata 
67
+# attribute equally called cell has in at least one sample 
68
+# of the 'join_data' dataset.
69
+# For each sample satisfying previous condition,only its regions that 
70
+# have a region attribute called pValue with the associated value 
71
+# less than 0.01 are conserved in output
73 72
 
74 73
 
75 74
 init_gmql()
... ...
@@ -36,7 +36,7 @@ seqnames,ranges ans strand and a variable part made up by the regions
36 36
 defined as input.
37 37
 The metadata and metadata_prefix are used to filter the data and choose 
38 38
 only the samples that match at least one metdatata with its prefix.
39
-The regions are shown for each sample obtained from filtering.
39
+The input regions are shown for each sample obtained from filtering.
40 40
 }
41 41
 \details{
42 42
 This function works only with datatset or Grangeslist that have the same 
... ...
@@ -26,12 +26,14 @@ It show a job log or traces a specific job
26 26
 If error occures a specific error is printed
27 27
 }
28 28
 \examples{
29
-\dontrun{
29
+
30 30
 remote_url = "http://genomic.elet.polimi.it/gmql-rest-r"
31 31
 login_gmql(remote_url)
32 32
 
33 33
 ## list all jobs
34 34
 list_jobs <- show_jobs_list(remote_url)
35
+
36
+\dontrun{
35 37
 jobs_1 <- list_jobs$jobs[[1]]
36 38
 
37 39
 ## show job log
... ...
@@ -28,7 +28,7 @@ After login you will receive an authentication token.
28 28
 As token remains vaild on server (until the next login / registration) 
29 29
 a user can safely use a token fora previous session as a convenience, 
30 30
 this token is saved in Global environment to perform subsequent REST call 
31
-even on complete R restart (if is environemnt has been saved, of course ...)
31
+even on complete R restart (if is environemnt has been saved)
32 32
 If error occures a specific error is printed
33 33
 }
34 34
 \examples{
... ...
@@ -37,6 +37,3 @@ remote_url = "http://genomic.elet.polimi.it/gmql-rest-r"
37 37
 login_gmql(remote_url)
38 38
 
39 39
 }
40
-\seealso{
41
-\code{\link{logout_gmql}}
42
-}
... ...
@@ -47,8 +47,8 @@ if both end with value.}
47 47
 }}
48 48
 }
49 49
 \value{
50
-GMQLDataset class object. It contains the value to use as input 
51
-for the subsequent GMQL function
50
+GMQLDataset object. It contains the value to use as input 
51
+for the subsequent GMQLDataset method
52 52
 }
53 53
 \description{
54 54
 Wrapper to GMQL map function
... ...
@@ -53,13 +53,10 @@ if both end with value.}
53 53
 }}
54 54
 }
55 55
 \value{
56
-GMQLDataset class object. It contains the value to use as input 
57
-for the subsequent GMQL function
56
+GMQLDataset object. It contains the value to use as input 
57
+for the subsequent GMQLDataset method
58 58
 }
59 59
 \description{
60
-Wrapper to GMQL join function
61
-}
62
-\details{
63 60
 It takes in input two datasets, respectively known as nchor (left) 
64 61
 and experiment (right) and returns a dataset of samples consisting of 
65 62
 regions extracted from the operands according to the specified condition
... ...
@@ -1,11 +1,8 @@
1 1
 % Generated by roxygen2: do not edit by hand
2 2
 % Please edit documentation in R/S3Operator.R
3
-\name{OPERATORS}
4
-\alias{OPERATORS}
3
+\name{META}
5 4
 \alias{META}
6
-\alias{OPERATORS}
7 5
 \alias{NIL}
8
-\alias{OPERATORS}
9 6
 \alias{SQRT}
10 7
 \title{OPERATOR object class constructor}
11 8
 \usage{
... ...
@@ -1,9 +1,7 @@
1 1
 % Generated by roxygen2: do not edit by hand
2 2
 % Please edit documentation in R/ordering-functions.R
3
-\name{ORDERING}
4
-\alias{ORDERING}
3
+\name{DESC}
5 4
 \alias{DESC}
6
-\alias{ORDERING}
7 5
 \alias{ASC}
8 6
 \title{Ordering functions}
9 7
 \usage{
... ...
@@ -12,14 +10,15 @@ DESC(...)
12 10
 ASC(...)
13 11
 }
14 12
 \arguments{
15
-\item{...}{Additional arguments for use in specific methods.}
13
+\item{...}{series of metatdata as string}
16 14
 }
17 15
 \value{
18 16
 ordering object
19 17
 }
20 18
 \description{
21 19
 These functions is used to create a series of metadata as string
22
-that require ordering on value.
20
+that require ordering on value; is used only in arrange method.
21
+(see example)
23 22
 }
24 23
 \details{
25 24
 \itemize{
... ...
@@ -4,7 +4,7 @@
4 4
 \alias{read}
5 5
 \alias{read_dataset}
6 6
 \alias{read}
7
-\title{GMQL Function: READ}
7
+\title{Function read}
8 8
 \usage{
9 9
 read_dataset(dataset, parser = "CustomParser", is_local = TRUE,
10 10
   is_GMQL = TRUE)
... ...
@@ -34,15 +34,13 @@ Default is CustomParser.}
34 34
 \item{samples}{GrangesList}
35 35
 }
36 36
 \value{
37
-DataSet class object. It contains the value to use as input 
38
-for the subsequent GMQL function
37
+GMQLDataset object. It contains the value to use as input 
38
+for the subsequent GMQLDataset method
39 39
 }
40 40
 \description{
41
-Read a GMQL dataset or any other folder containig some homogenus sample
42
-from disk, saving in Scala memory that can be referenced in R
41
+Read a GMQL dataset, folder containig some homogenus sample from disk 
42
+or GrangesList saving in Scala memory that can be referenced in R.
43 43
 Also used to read a repository dataset in case of remote processing.
44
-
45
-Read a GrangesList saving in scala memory that can be referenced in R
46 44
 }
47 45
 \details{
48 46
 Normally a GMQL dataset contains an XML schema file that contains
... ...
@@ -50,6 +48,13 @@ name of column header. (e.g chr, start, stop, strand)
50 48
 The CustomParser read this XML schema; 
51 49
 if you already know what kind of schema your files are, use one of the 
52 50
 parser defined without reading any XML schema
51
+
52
+If GrangesList has no metadata: i.e. metadata() is empty, two metadata are
53
+generated.
54
+\itemize{
55
+\item{"Provider" = "Polimi"}
56
+\item{"Application" = "RGMQL"}
57
+}
53 58
 }
54 59
 \examples{
55 60
 
... ...
@@ -66,7 +71,7 @@ test_path <- system.file("example", "DATASET", package = "RGMQL")
66 71
 r = read_dataset(test_path,"ANNParser")
67 72
 
68 73
 ## read remote public dataset stored into GMQL system repository 
69
-
74
+## If public dataset a prefix "public." is needed before dataset name
70 75
 r2 = read_dataset("public.HG19_TCGA_dnaseq",is_local = FALSE)
71 76
 
72 77
 }
... ...
@@ -18,12 +18,12 @@ It allows to enable or disable remote processing
18 18
 }
19 19
 \details{
20 20
 The invocation of this function allow to change mode of processing.
21
-after materialization is not possbile to switch the processing mode,
21
+after invoking collect() is not possbile to switch the processing mode,
22 22
 }
23 23
 \examples{
24 24
 
25 25
 # initialize with remote processing off
26
-init_gmql("tab",remote_processing=FALSE)
26
+init_gmql("tab",remote_processing = FALSE)
27 27
 
28 28
 # change processing mode to remote
29 29
 remote_processing(TRUE)
... ...
@@ -12,7 +12,7 @@ select(.data, ...)
12 12
 
13 13
 \S4method{select}{GMQLDataset}(.data, metadata = NULL,
14 14
   metadata_update = NULL, all_but_meta = FALSE, regions = NULL,
15
-  regions_update = NULL, all_but_reg = FALSE)
15
+  regions_update = NULL, all_but_reg = FALSE, ...)
16 16
 }
17 17
 \arguments{
18 18
 \item{.data}{GMQLDataset class object}
... ...
@@ -54,21 +54,20 @@ are all except ones include in region parameter.
54 54
 if regions is not defined \emph{all_but_reg} is not considerd.}
55 55
 }
56 56
 \value{
57
-GMQLDataset class object. It contains the value to use as input 
58
-for the subsequent GMQL function
57
+GMQLDataset object. It contains the value to use as input 
58
+for the subsequent GMQLDataset method
59 59
 }
60 60
 \description{
61 61
 Wrapper to GMQL project function
62 62
 
63 63
 It creates, from an existing dataset, a new dataset with all the samples 
64 64
 from input dataset, but keeping for each sample in the input dataset 
65
-only those metadata and/or region attributes expressed in the operator 
66
-parameter list.
65
+only those metadata and/or region attributes expressed.
67 66
 Region coordinates and values of the remaining metadata remain equal to 
68 67
 those in the input dataset. It allows to:
69 68
 \itemize{
70 69
 \item{Remove existing metadata and/or region attributes from a dataset}
71
-\item{Create new metadata and/or region attributes in the result}
70
+\item{Update new metadata and/or region attributes in the result}
72 71
 }
73 72
 }
74 73
 \examples{
... ...
@@ -14,8 +14,7 @@ considering semi_join NOT IN semi_join_dataset, F => semijoin is performed
14 14
 considering semi_join IN semi_join_dataset}
15 15
 
16 16
 \item{...}{Additional arguments for use in specific methods.
17
-
18
-This method accept a function to define condition evaluation on metadata.
17
+It is also accpet a functions to define condition evaluation on metadata.
19 18
 \itemize{
20 19
 \item{\code{\link{FN}}: Fullname evaluation, two attributes match 
21 20
 if they both end with value and, if they have a further prefixes,
... ...
@@ -33,3 +32,26 @@ semijoin condition as list
33 32
 This function is use as support to filter method to define 
34 33
 semijoin conditions on metadata
35 34
 }
35
+\examples{
36
+
37
+# It creates a new dataset called 'jun_tf' by selecting those samples and 
38
+# their regions from the existing 'data' dataset such that:
39
+# Each output sample has a metadata attribute called antibody_target 
40
+# with value JUN.
41
+# Each output sample also has not a metadata attribute called "cell" 
42
+# that has the same value of at least one of the values that a metadata 
43
+# attribute equally called cell has in at least one sample 
44
+# of the 'join_data' dataset.
45
+# For each sample satisfying previous condition,only its regions that 
46
+# have a region attribute called pValue with the associated value 
47
+# less than 0.01 are conserved in output
48
+
49
+
50
+init_gmql()
51
+test_path <- system.file("example", "DATASET", package = "RGMQL")
52
+test_path2 <- system.file("example", "DATASET_GDM", package = "RGMQL")
53
+data <- read_dataset(test_path)
54
+join_data <-  read_dataset(test_path2)
55
+jun_tf <- filter(data,NULL,NULL, semijoin(join_data, TRUE, DF("cell")))
56
+
57
+}
... ...
@@ -34,17 +34,16 @@ left_input_data that overlap with at least one region in right_input_data
34 34
 (even just one base).}
35 35
 }
36 36
 \value{
37
-GMQLDataset class object. It contains the value to use as input 
38
-for the subsequent GMQL function
37
+GMQLDataset object. It contains the value to use as input 
38
+for the subsequent GMQLDataset method
39 39
 }
40 40
 \description{
41 41
 Wrapper to GMQL difference function
42
-}
43
-\details{
44
-It produces one sample in the result for each sample of the left operand,
45
-by keeping the same metadata of the left input sample and only those 
46
-regions (with their schema and values) of the left input sample which 
47
-do not intersect with any region in the right operand sample.
42
+
43
+It produces one sample in the result for each sample of the 
44
+left operand, by keeping the same metadata of the left input sample 
45
+and only those regions (with their schema and values) of the left input 
46
+sample which do not intersect with any region in the right operand sample.
48 47
 The optional \emph{joinby} clause is used to extract a subset of couples
49 48
 from the cartesian product of two dataset \emph{x} and \emph{y} 
50 49
 on which to apply the DIFFERENCE operator:
... ...
@@ -18,7 +18,8 @@ Every job in the list is identified by:
18 18
 }
19 19
 }
20 20
 \description{
21
-It show all Jobs (run, succeded or failed) invoked by user
21
+It show all Jobs (run, succeded or failed) invoked by user using the proper 
22
+GMQL web service available on a remote server
22 23
 }
23 24
 \details{
24 25
 If error occures a specific error is printed
... ...
@@ -19,13 +19,14 @@ Every query in the list is identified by:
19 19
 }
20 20
 }
21 21
 \description{
22
-It shows all the GMQL query saved on repository 
23
-using the proper GMQL web service available on a remote server
22
+It shows all the GMQL query saved on repository using the proper GMQL 
23
+web service available on a remote server
24 24
 }
25 25
 \details{
26 26
 if error occures, a specific error is printed
27 27
 }
28 28
 \examples{
29
+
29 30
 remote_url = "http://genomic.elet.polimi.it/gmql-rest-r"
30 31
 login_gmql(remote_url)
31 32
 list <- show_queries_list(remote_url)
... ...
@@ -27,9 +27,9 @@ GrangesList with associated metadata
27 27
 GMQL Operation: TAKE
28 28
 
29 29
 It saves the contents of a dataset that contains samples metadata 
30
-and samples regions.
31
-It is normally used to store in memoery the contents of any dataset 
32
-generated during a GMQL query. the operation can be very time-consuming.
30
+and samples regions as GrangesList.
31
+It is normally used to store in memory the contents of any dataset 
32
+generated during a GMQL query. The operation can be very time-consuming.
33 33
 If you have invoked any materialization before take function, 
34 34
 all those dataset will be materialized as folder.
35 35
 }
... ...
@@ -9,21 +9,20 @@
9 9
 \S4method{union}{GMQLDataset,GMQLDataset}(x, y)
10 10
 }
11 11
 \arguments{
12
-\item{x}{GMQLDataset class object}
12
+\item{x}{GMQLDataset object}
13 13
 
14
-\item{y}{GMQLDataset class object}
14
+\item{y}{GMQLDataset object}
15 15
 }
16 16
 \value{
17
-GMQLDataset class object. It contains the value to use as input 
18
-for the subsequent GMQL function
17
+GMQLDataset object. It contains the value to use as input 
18
+for the subsequent GMQLDataset method
19 19
 }
20 20
 \description{
21 21
 Wrapper to GMQL union function
22
-}
23
-\details{
24
-It is used to integrate homogeneous or heterogeneous samples of two datasets 
25
-within a single dataset; for each sample of either input dataset, 
26
-a result sample is created as follows:
22
+
23
+It is used to integrate homogeneous or heterogeneous samples 
24
+of two datasets within a single dataset; for each sample of either input 
25
+dataset, a result sample is created as follows:
27 26
 \itemize{
28 27
 \item {Metadata are the same as in the original sample.}
29 28
 \item {Resulting schema is obtained by projecting the schema