@@ -35,4 +35,4 @@ setMethod("show", "GMQLDataset",

                 cat(" value :",paste(object@value))

             })

-#object <- as.list(substitute(list(...)))[-1L]

+

@@ -5,7 +5,7 @@

 #' defined as input.

 #' The metadata and metadata_prefix are used to filter the data and choose 

 #' only the samples that match at least one metdatata with its prefix.

-#' The regions are shown for each sample obtained from filtering.

+#' The input regions are shown for each sample obtained from filtering.

 #'

 #' @import xml2

 #' @importFrom dplyr bind_cols

@@ -36,7 +36,6 @@

 #'

 #' @examples

 #' 

-#' \dontrun{

 #' library(GenomicRanges)

 #' gr1 <- GRanges(seqnames = "chr2", ranges = IRanges(3, 6), strand = "+", 

 #' score = 5L, GC = 0.45)

@@ -46,7 +45,8 @@

 #' grl = GRangesList(gr1, gr2)

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

 #' export_gmql(grl, test_out_path,TRUE)

-#' }

+#' 

+#' 

 #' @export

 #'

 export_gmql <- function(samples, dir_out, is_gtf)

@@ -158,7 +158,8 @@ take_value.META_AGGREGATES <- function(obj){

 #' res = extend(exp, m_score = MEDIAN("score"))

 #' 

 #' 

-#' @name AGGREGATES

+#' @name SUM

+#' @aliases SUM

 #' @rdname aggr-class

 #' @export

 #'

@@ -172,7 +173,8 @@ SUM <- function(value)

     return(list)

 }

-#' @name AGGREGATES

+#' @name MIN

+#' @aliases MIN

 #' @rdname aggr-class

 #' @export

 #'

@@ -187,7 +189,8 @@ MIN <- function(value)

 }

-#' @name AGGREGATES 

+#' @name MAX

+#' @aliases MAX

 #' @rdname aggr-class 

 #' @export

 #'

@@ -201,7 +204,8 @@ MAX <- function(value)

     return(list)

 }

-#' @name AGGREGATES

+#' @name AVG

+#' @aliases AVG

 #' @rdname aggr-class

 #' @export

 #'

@@ -215,7 +219,8 @@ AVG <- function(value)

     return(list)

 }

-#' @name AGGREGATES

+#' @name BAG

+#' @aliases BAG

 #' @rdname aggr-class

 #' @export

 #'

@@ -229,7 +234,8 @@ BAG <- function(value)

     return(list)

 }

-#' @name AGGREGATES

+#' @name COUNT

+#' @aliases COUNT

 #' @rdname aggr-class

 #' @export

 #'

@@ -246,7 +252,8 @@ as.character.COUNT <- function(obj) {

 }

 check.COUNT <- function(obj){}

-#' @name AGGREGATES

+#' @name STD

+#' @aliases STD

 #' @rdname aggr-class

 #' @export

 #'

@@ -261,7 +268,8 @@ STD <- function(value)

 }

-#' @name AGGREGATES

+#' @name MEDIAN

+#' @aliases MEDIAN

 #' @rdname aggr-class

 #' @export

 #'

@@ -275,7 +283,8 @@ MEDIAN <- function(value)

     return(list)

 }

-#' @name AGGREGATES

+#' @name Q1

+#' @aliases Q1

 #' @rdname aggr-class

 #' @export

 #'

@@ -289,7 +298,8 @@ Q1 <- function(value)

     return(list)

 }

-#' @name AGGREGATES

+#' @name Q2

+#' @aliases Q2

 #' @rdname aggr-class

 #' @export

 #'

@@ -302,7 +312,8 @@ Q2 <- function(value)

     return(list)

 }

-#' @name AGGREGATES

+#' @name Q3

+#' @aliases Q3

 #' @rdname aggr-class

 #' @export

 #'

@@ -316,7 +327,8 @@ Q3 <- function(value)

     return(list)

 }

-#' @name AGGREGATES

+#' @name BAGD

+#' @aliases BAGD

 #' @rdname aggr-class

 #' @export

 #'

@@ -52,7 +52,8 @@ print.PARAMETER <- function(obj){

 #' 

 #' res = cover(exp, 2, ANY()+2/3)

 #' 

-#' @name COVER-PARAMETER

+#' @name ALL

+#' @aliases ALL

 #' @rdname cover-param-class

 #' @export

 #'

@@ -64,7 +65,8 @@ ALL <- function()

     return(list)

 }

-#' @name COVER-PARAMETER

+#' @name ANY

+#' @aliases ANY

 #' @rdname cover-param-class

 #' @export

 #'

@@ -101,7 +101,8 @@ check.DISTAL <- function(value)

 #' genometric_predicate = list(list(MD(1), DGE(12000), DOWN())), 

 #' DF("provider"), region_output = "RIGHT")

 #'

-#' @name DISTAL

+#' @name DL

+#' @aliases DL

 #' @rdname distal-class

 #' @export

 #' 

@@ -114,7 +115,8 @@ DL <- function(value)

     return(list)

 }

-#' @name DISTAL

+#' @name DG

+#' @aliases DG

 #' @rdname distal-class

 #' @export

 #' 

@@ -127,7 +129,8 @@ DG <- function(value)

     return(list)

 }

-#' @name DISTAL

+#' @name DLE

+#' @aliases DLE

 #' @rdname distal-class

 #' @export

 #' 

@@ -140,7 +143,8 @@ DLE <- function(value)

     return(list)

 }

-#' @name DISTAL

+#' @name DGE

+#' @aliases DGE

 #' @rdname distal-class

 #' @export

 #' 

@@ -153,7 +157,8 @@ DGE <- function(value)

     return(list)

 }

-#' @name DISTAL

+#' @name MD

+#' @aliases MD

 #' @rdname distal-class

 #' @export

 #' 

@@ -167,7 +172,8 @@ MD <- function(value)

 }

-#' @name DISTAL

+#' @name UP

+#' @aliases UP

 #' @rdname distal-class

 #' @export

 #' 

@@ -184,7 +190,8 @@ as.character.UP <- function(obj) {

 }

-#' @name DISTAL

+#' @name DOWN

+#' @aliases DOWN

 #' @rdname distal-class

 #' @export

 #' 

@@ -87,7 +87,8 @@ as.character.OPERATOR <- function(obj) {

 #' exp = read_dataset(test_path)

 #' out = select(exp, metadata_update = list(concSq = SQRT("concentration")))

 #' 

-#' @name OPERATORS

+#' @name META

+#' @aliases META

 #' @rdname operator-class

 #' @export

 #'

@@ -122,7 +123,8 @@ check.META <- function(type)

 }

-#' @name OPERATORS

+#' @name NIL

+#' @aliases NIL

 #' @rdname operator-class

 #' @export

 #'

@@ -145,7 +147,8 @@ check.NIL <- function(value)

 }

-#' @name OPERATORS

+#' @name SQRT

+#' @aliases SQRT

 #' @rdname operator-class

 #' @export

 #'

@@ -29,7 +29,8 @@

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

 #' r = read_dataset(test_path)

 #' 

-#' @name evaluation

+#' @name FN

+#' @aliases FN

 #' @rdname condition_eval_func

 #' @export

 FN <- function(...)

@@ -49,7 +50,8 @@ FN <- function(...)

     join_condition_matrix

 }

-#' @name evaluation

+#' @name EX

+#' @aliases EX

 #' @rdname condition_eval_func

 #' @export

 EX <- function(...)

@@ -69,7 +71,8 @@ EX <- function(...)

     join_condition_matrix

 }

-#' @name evaluation

+#' @name DF

+#' @aliases DF

 #' @rdname condition_eval_func

 #' @export

 DF <- function(...)

@@ -1,4 +1,4 @@

-#' GMQL Operation: COVER

+#' Method cover

 #'

 #' It takes as input a dataset containing one or more samples and returns 

 #' another dataset (with a single sample, if no \emph{groupby} option is 

@@ -84,21 +84,21 @@

 #' @param variation string identifying the cover GMQL function variation.

 #' The admissible string are:

 #' \itemize{

-#' \item{flat: returns the contiguous region that starts from the first end 

+#' \item{FLAT: returns the contiguous region that starts from the first end 

 #' and stops at the last end of the regions which would contribute 

 #' to each region of the \emph{cover}.}

-#' \item{summit: returns regions that start from a position

+#' \item{SUMMIT: returns regions that start from a position

 #' where the number of intersecting regions is not increasing afterwards and

 #' stops at a position where either the number of intersecting regions 

 #' decreases, or it violates the max accumulation index.}

-#' \item{histogram: returns the non-overlapping regions contributing to 

+#' \item{HISTOGRAM: returns the non-overlapping regions contributing to 

 #' the cover, each with its accumulation index value, which is assigned to 

 #' the AccIndex region attribute.}

-#' \item{cover: default value.}

+#' \item{COVER: default value.}

 #' }

 #' 

-#' @return GMQLDataset class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #' 

 #' @examples

 #' 

@@ -1,11 +1,11 @@

 #' Method setdiff

 #' 

-#' Wrapper to GMQL difference function

+#' @description Wrapper to GMQL difference function

 #' 

-#' It produces one sample in the result for each sample of the left operand,

-#' by keeping the same metadata of the left input sample and only those 

-#' regions (with their schema and values) of the left input sample which 

-#' do not intersect with any region in the right operand sample.

+#' @description It produces one sample in the result for each sample of the 

+#' left operand, by keeping the same metadata of the left input sample 

+#' and only those regions (with their schema and values) of the left input 

+#' sample which do not intersect with any region in the right operand sample.

 #' The optional \emph{joinby} clause is used to extract a subset of couples

 #' from the cartesian product of two dataset \emph{x} and \emph{y} 

 #' on which to apply the DIFFERENCE operator:

@@ -38,8 +38,8 @@

 #' left_input_data that overlap with at least one region in right_input_data 

 #' (even just one base).

 #' 

-#' @return GMQLDataset class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #' 

 #'

 #' @examples

@@ -1,8 +1,8 @@

-#' GMQL Operation: EXTEND

+#' Method extend

 #'

-#' It generates new metadata attributes as result of aggregate functions 

-#' applied to sample region attributes and adds them to the existing metadata 

-#' attributes of the sample.

+#' For each sample in an input dataset, it generates new metadata attributes 

+#' as result of aggregate functions applied to sample region attributes 

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

 #' Aggregate functions are applied sample by sample.

 #'

 #' @importFrom rJava .jnull

@@ -11,8 +11,7 @@

 #'

 #' @param .data GMQLDataset class object 

 #' @param ... Additional arguments for use in specific methods.

-#' 

-#' This method accept a series of aggregate function on region attribute.

+#' It accept a series of aggregate function on region attribute.

 #' All the element in the form \emph{key} = \emph{aggregate}.

 #' The \emph{aggregate} is an object of class AGGREGATES

 #' The aggregate functions available are: \code{\link{SUM}}, 

@@ -30,8 +29,8 @@

 #' }

 #' "mixed style" is not allowed

 #'

-#' @return GMQLDataset class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #' 

 #' @examples

 #'

@@ -1,6 +1,4 @@

 #' Method merge

-#' 

-#' Wrapper to GMQL join function

 #'

 #' It takes in input two datasets, respectively known as nchor (left) 

 #' and experiment (right) and returns a dataset of samples consisting of 

@@ -57,8 +55,8 @@

 #' the genometric predicate)}

 #' }

 #'

-#' @return GMQLDataset class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #' 

 #' @examples

 #' 

@@ -1,4 +1,4 @@

-#' GMQL Operation: MAP

+#' Method map

 #'

 #' It computes, for each sample in the right dataset, aggregates over the 

 #' values of the right regions that intersect with a region in a left sample, 

@@ -52,8 +52,8 @@

 #' if both end with value.}

 #' }

 #' 

-#' @return GMQLDataset class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #' 

 #' @examples

 #'

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

 #' GMQL Function: EXECUTE

 #'

 #' Execute GMQL query.

-#' The function works only after invoking at least one materialize

+#' The function works only after invoking at least one collect

 #' 

 #' @importFrom rJava J

 #' 

@@ -67,7 +67,9 @@ execute <- function()

-#' GMQL Operation: MATERIALIZE

+#' Method collect

+#' 

+#' Wrapper to GMQL materialize function

 #'

 #' It saves the contents of a dataset that contains samples metadata and 

 #' samples regions.

@@ -124,12 +126,12 @@ gmql_materialize <- function(input_data, dir_out, name)

 }

-#' GMQL Operation: TAKE

+#' Method take

 #'

 #' It saves the contents of a dataset that contains samples metadata 

-#' and samples regions.

-#' It is normally used to store in memoery the contents of any dataset 

-#' generated during a GMQL query. the operation can be very time-consuming.

+#' and samples regions as GrangesList.

+#' It is normally used to store in memory the contents of any dataset 

+#' generated during a GMQL query. The operation can be very time-consuming.

 #' If you have invoked any materialization before take function, 

 #' all those dataset will be materialized as folder.

 #'

@@ -1,13 +1,14 @@

-#' GMQL Operation: MERGE

-#'

+#' Method aggregate

+#' 

 #' It builds a dataset consisting of a single sample having as many regions as

 #' the number of regions of the input data and as many metadata as the union of

-#' the 'attribute-value' tuples of the input samples. A groupby clause can be

-#' specified on metadata: the samples are then partitioned in groups, each with

-#' a distinct value of the grouping metadata attributes. The operation is

-#' separately applied to each group, yielding one sample in the result for each

-#' group. Samples whose names are not present in the grouping metadata

-#' parameter are disregarded.

+#' the 'attribute-value' tuples of the input samples. 

+#' If at least one evaluation function is specified: the samples are then 

+#' partitioned in groups, each with a distinct value of the grouping metadata 

+#' attributes. The operation is separately applied to each group, yielding 

+#' one sample in the result for each group. 

+#' Samples whose names are not present in the grouping metadata parameter 

+#' are disregarded.

 #'

 #' @importFrom rJava J

 #' @importFrom rJava .jnull

@@ -15,8 +16,7 @@

 #'

 #' @param x GMQLDataset class object

 #' @param ... Additional arguments for use in specific methods.

-#'

-#' list of evalation function to define condition evaluation on metadata:

+#' It accepts a list of evalation function to define evaluation on metadata:

 #' \itemize{

 #' \item{\code{\link{FN}}: Fullname evaluation, two attributes match 

 #' if they both end with value and, if they have a further prefixes,

@@ -27,8 +27,8 @@

 #' if both end with value.}

 #' }

 #' 

-#' @return DataSet class object. It contains the value to use as input for the

-#'   subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #'

 #' @examples

 #'

@@ -1,28 +1,22 @@

-#' GMQL operation: ORDER

+#' Method arrange

 #'

 #' It is used to order either samples or sample regions or both, according to 

 #' a set of metadata and/or region attributes, and/or region coordinates.

 #' Order can be specified as ascending / descending for every attribute

 #' The number of samples and their regions remain the same 

-#' (unless mtop/rtop parameters specified) but a new ordering metadata 

+#' (unless fetching options are specified) but a new ordering metadata 

 #' and/or region attribute is added.

 #' Sorted samples or regions have a new attribute "order", 

-#' added to either metadata, or regions, or both of them as specified in input

-#' The input mtop = k and rtop = m extracts the first k samples 

-#' and m regions respectively, the clause mtopg = k and rtopg = m 

-#' performs grouping operation, grouping by identical values 

-#' of ordering attributes and then selects the first k samples 

-#' or regions of each group

+#' added to either metadata, or regions, or both of them as specified in inputs

 #'

 #' @importFrom rJava J

 #' @importFrom rJava .jnull

 #' @importFrom rJava .jarray

 #' 

 #' @param .data GMQLDataset class object

-#' @param metadata_ordering list of order objects where every object 

-#' contains the name of metadata.

-#' The ORDER's available are: \code{\link{ASC}}, \code{\link{DESC}}

-#' Every condition accepts only one string value. (e.g. ASC("cell_type") )

+#' @param metadata_ordering list of ordering function contains name of 

+#' metadata.

+#' The function available are: \code{\link{ASC}}, \code{\link{DESC}}

 #' 

 #' @param fetch_opt string indicating the option used to fetch the 

 #' first k sample:

@@ -36,10 +30,9 @@

 #' @param num_fetch integer value identifying the number of region to fetch

 #' by default is 0, that's means all sample are fetched

 #' s

-#' @param regions_ordering list of ORDER objects where every object contains 

-#' the name of region schema value.

-#' The ORDER's available are: \code{\link{ASC}}, \code{\link{DESC}}.

-#' Every condition accepts only one string value. (e.g. DESC("pvalue") )

+#' @param regions_ordering list of ordering function contains 

+#' name of region schema value.

+#' The function available are: \code{\link{ASC}}, \code{\link{DESC}}.

 #' 

 #' @param reg_fetch_opt string indicating the option used to fetch the 

 #' first k regions:

@@ -54,10 +47,8 @@

 #' by default is 0, that's means all regions are fetched

 #' @param ... Additional arguments for use in specific methods.

 #' 

-#' 

-#' @return DataSet class object. It contains the value to use as input 

-#' for the subsequent GMQL function

-#' 

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #'

 #' @examples

 #' 

@@ -1,16 +1,15 @@

-#' GMQL Operation: PROJECT

+#' Method select

 #'

 #' It creates, from an existing dataset, a new dataset with all the samples 

 #' from input dataset, but keeping for each sample in the input dataset 

-#' only those metadata and/or region attributes expressed in the operator 

-#' parameter list.

+#' only those metadata and/or region attributes expressed.

 #' Region coordinates and values of the remaining metadata remain equal to 

 #' those in the input dataset. It allows to:

 #' \itemize{

 #' \item{Remove existing metadata and/or region attributes from a dataset}

-#' \item{Create new metadata and/or region attributes in the result}

+#' \item{Update new metadata and/or region attributes in the result}

 #' }

-#'

+#' 

 #' @importFrom rJava J

 #' @importFrom rJava .jnull

 #' @importFrom rJava .jarray

@@ -48,8 +47,8 @@

 #' 

 #' @param ... Additional arguments for use in specific methods.

 #' 

-#' @return GMQLDataset class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #'

 #' @examples

 #' 

@@ -94,7 +93,7 @@

 setMethod("select", "GMQLDataset",

             function(.data, metadata = NULL, metadata_update = NULL, 

                         all_but_meta = FALSE, regions = NULL, 

-                        regions_update = NULL, all_but_reg=FALSE)

+                        regions_update = NULL, all_but_reg = FALSE, ...)

             {

                 data = .data@value

                 r_update <- substitute(regions_update)

@@ -22,7 +22,7 @@

 #' You can always perform it, calling the function \code{\link{login_gmql}} 

 #' explicitly

 #' 

-#' @param username string name used during signup

+#' @param username string name used during signup 

 #' @param password string password used during signup

 #' 

 #' @return None

@@ -62,10 +62,10 @@ init_gmql <- function(output_format = "gtf", remote_processing = FALSE,

     WrappeR$initGMQL(out_format,remote_processing)

 }

-#' GMQL Function: READ

+#' Function read

 #'

-#' Read a GMQL dataset or any other folder containig some homogenus sample

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

+#' Read a GMQL dataset, folder containig some homogenus sample from disk 

+#' or GrangesList saving in Scala memory that can be referenced in R.

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

 #' 

 #' @importFrom rJava .jnull

@@ -89,8 +89,8 @@ init_gmql <- function(output_format = "gtf", remote_processing = FALSE,

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

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

 #' 

-#' @return DataSet class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #' 

 #' @details

 #' Normally a GMQL dataset contains an XML schema file that contains

@@ -98,6 +98,13 @@ init_gmql <- function(output_format = "gtf", remote_processing = FALSE,

 #' The CustomParser read this XML schema; 

 #' if you already know what kind of schema your files are, use one of the 

 #' parser defined without reading any XML schema

+#' 

+#' If GrangesList has no metadata: i.e. metadata() is empty, two metadata are

+#' generated.

+#' \itemize{

+#' \item{"Provider" = "Polimi"}

+#' \item{"Application" = "RGMQL"}

+#' }

 #'

 #' @examples

 #' 

@@ -114,7 +121,7 @@ init_gmql <- function(output_format = "gtf", remote_processing = FALSE,

 #' r = read_dataset(test_path,"ANNParser")

 #' 

 #' ## read remote public dataset stored into GMQL system repository 

-#' 

+#' ## If public dataset a prefix "public." is needed before dataset name

 #' r2 = read_dataset("public.HG19_TCGA_dnaseq",is_local = FALSE)

 #' 

 #' }

@@ -179,17 +186,13 @@ read_dataset <- function(dataset, parser = "CustomParser", is_local=TRUE,

         GMQLDataset(data)

 }

-#' GMQL Function: READ

-#'

-#' Read a GrangesList saving in scala memory that can be referenced in R

-#'

+

 #' @importFrom S4Vectors metadata

 #' @importFrom rJava J

 #' @importFrom rJava .jarray

 #' 

 #' @param samples GrangesList

 #' 

-#' 

 #' @name read

 #' @rdname read-function

 #' @export

@@ -274,11 +277,11 @@ We provide two metadata for you")

 #' Disable or Enable remote processing

 #'

-#' It allows to enable or disable remote processing

+#' It allows to enable or disable remote processing 

 #' 

 #' @details 

 #' The invocation of this function allow to change mode of processing.

-#' after materialization is not possbile to switch the processing mode, 

+#' after invoking collect() is not possbile to switch the processing mode, 

 #' 

 #' @importFrom rJava J

 #' 

@@ -290,7 +293,7 @@ We provide two metadata for you")

 #' @examples

 #' 

 #' # initialize with remote processing off

-#' init_gmql("tab",remote_processing=FALSE)

+#' init_gmql("tab",remote_processing = FALSE)

 #' 

 #' # change processing mode to remote

 #' remote_processing(TRUE)

@@ -1,13 +1,13 @@

-#' GMQL Operation: SELECT

-#'

-#' It returns all the samples satisfying the predicate on metadata.

-#' If regions are specified, returns regions satisfying the predicate 

-#' on regions.

-#' If semijoin clauses are specified they are applied, too.

-#' When semijoin is defined, it extracts those samples containing all metadata 

-#' attribute defined in semijoin clause with at least one metadata value 

-#' in common with semi join dataset.

-#' If no metadata in common between input dataset and semi join dataset, 

+#' Method filter

+#' 

+#' It creates a new dataset from an existing one by extracting a subset of 

+#' samples and/or regions from the input dataset according to their predicate.

+#' each sample in the output dataset has the same region attributes, 

+#' values, and metadata as in the input dataset.

+#' When semijoin function is defined, it extracts those samples containing 

+#' all metadata attribute defined in semijoin clause with at least 

+#' one metadata value in common with semijoin dataset.

+#' If no metadata in common between input dataset and semijoin dataset, 

 #' no sample is extracted.

 #'

 #' @importFrom rJava J

@@ -20,16 +20,15 @@

 #' on metadata attribute. 

 #' Only !, |, ||, &, && are admitted.

 #' @param r_predicate logical predicate made up by R logical operation 

-#' on chema region values. 

+#' on schema region values. 

 #' Only !, |, ||, &, && are admitted.

 #' @param ... Additional arguments for use in specific methods.

-#' 

-#' @param semijoin \code{\link{semijoin}} function 

+#' It is also accept \code{\link{semijoin}} function 

 #' to define filter method with semijoin condition (see examples).

 #' 

 #' 

-#' @return GMQLDataset class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #' 

 #' @examples

 #' 

@@ -43,17 +42,17 @@

 #' 

 #' \dontrun{

 #' 

-#' It creates a new dataset called 'jun_tf' by selecting those samples and 

-#' their regions from the existing 'data' dataset such that:

-#' Each output sample has a metadata attribute called antibody_target 

-#' with value JUN.

-#' Each output sample also has not a metadata attribute called "cell" 

-#' that has the same value of at least one of the values that a metadata 

-#' attribute equally called cell has in at least one sample 

-#' of the 'join_data' dataset.

-#' For each sample satisfying previous condition,only its regions that 

-#' have a region attribute called pValue with the associated value 

-#' less than 0.01 are conserved in output

+#' # It creates a new dataset called 'jun_tf' by selecting those samples and 

+#' # their regions from the existing 'data' dataset such that:

+#' # Each output sample has a metadata attribute called antibody_target 

+#' # with value JUN.

+#' # Each output sample also has not a metadata attribute called "cell" 

+#' # that has the same value of at least one of the values that a metadata 

+#' # attribute equally called cell has in at least one sample 

+#' # of the 'join_data' dataset.

+#' # For each sample satisfying previous condition,only its regions that 

+#' # have a region attribute called pValue with the associated value 

+#' # less than 0.01 are conserved in output

 #' 

 #' 

 #' init_gmql()

@@ -131,8 +130,7 @@ gmql_select <- function(input_data, predicate, region_predicate, s_join)

 #' considering semi_join IN semi_join_dataset

 #' 

 #' @param ... Additional arguments for use in specific methods.

-#' 

-#' This method accept a function to define condition evaluation on metadata.

+#' It is also accpet a functions to define condition evaluation on metadata.

 #' \itemize{

 #' \item{\code{\link{FN}}: Fullname evaluation, two attributes match 

 #' 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)

 #' if both end with value.}

 #' }

 #' 

+#' @examples

+#' 

+#' # It creates a new dataset called 'jun_tf' by selecting those samples and 

+#' # their regions from the existing 'data' dataset such that:

+#' # Each output sample has a metadata attribute called antibody_target 

+#' # with value JUN.

+#' # Each output sample also has not a metadata attribute called "cell" 

+#' # that has the same value of at least one of the values that a metadata 

+#' # attribute equally called cell has in at least one sample 

+#' # of the 'join_data' dataset.

+#' # For each sample satisfying previous condition,only its regions that 

+#' # have a region attribute called pValue with the associated value 

+#' # less than 0.01 are conserved in output

+#' 

+#' 

+#' init_gmql()

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

+#' test_path2 <- system.file("example", "DATASET_GDM", package = "RGMQL")

+#' data <- read_dataset(test_path)

+#' join_data <-  read_dataset(test_path2)

+#' jun_tf <- filter(data,NULL,NULL, semijoin(join_data, TRUE, DF("cell")))

+#' 

 #' @return semijoin condition as list

 #' @export

-#' 

 semijoin <- function(data, not_in = FALSE, ...)

 {

     semij_cond = list(...)

@@ -1,10 +1,10 @@

 #' Method union

 #' 

-#' Wrapper to GMQL union function

+#' @description Wrapper to GMQL union function

 #' 

-#' It is used to integrate homogeneous or heterogeneous samples of two datasets 

-#' within a single dataset; for each sample of either input dataset, 

-#' a result sample is created as follows:

+#' @description It is used to integrate homogeneous or heterogeneous samples 

+#' of two datasets within a single dataset; for each sample of either input 

+#' dataset, a result sample is created as follows:

 #' \itemize{

 #' \item {Metadata are the same as in the original sample.}

 #' \item {Resulting schema is obtained by projecting the schema 

@@ -23,11 +23,11 @@

 #' 

 #' @importFrom rJava J

 #' 

-#' @param x GMQLDataset class object

-#' @param y GMQLDataset class object 

+#' @param x GMQLDataset object

+#' @param y GMQLDataset object 

 #'

-#' @return GMQLDataset class object. It contains the value to use as input 

-#' for the subsequent GMQL function

+#' @return GMQLDataset object. It contains the value to use as input 

+#' for the subsequent GMQLDataset method

 #'

 #' @examples

 #'