select.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gmql_project.R
\name{select}
\alias{select}
\alias{select,GMQLDataset-method}
\alias{select-method}
\title{Method select}
\usage{
\S4method{select}{GMQLDataset}(
  .data,
  metadata = NULL,
  metadata_update = NULL,
  all_but_meta = FALSE,
  regions = NULL,
  regions_update = NULL,
  all_but_reg = FALSE
)
}
\arguments{
\item{.data}{GMQLDataset class object}

\item{metadata}{vector of strings made up by metadata attributes}

\item{metadata_update}{list of updating rules in the form of 
key = value generating new metadata attributes and/or attribute values.
The following options are available:
\itemize{
\item{All aggregation functions already defined by AGGREGATES object}
\item{All basic mathematical operations (+, -, *, /), including parenthesis}
\item{SQRT constructor object defined by OPERATOR object}
}}

\item{all_but_meta}{logical value indicating which metadata 
you want to exclude; If FALSE, only the metadata attributes specified in 
\emph{metadata} argument are kept in the output of the operation; if TRUE, 
the metadata are all kept except those in \emph{metadata} argument.
If \emph{metadata} input parameter is not defined \emph{all_but_meta} 
is not considerd.}

\item{regions}{vector of strings made up by region attributes}

\item{regions_update}{list of updating rules in the form of 
key = value generating new genomic region attributes and/or values.
The following options are available:
\itemize{
\item{All aggregation functions already defined by AGGREGATES object}
\item{All basic mathematical operations (+, -, *, /), including parenthesis}
\item{SQRT, META, NIL constructor objects defined by OPERATOR object}
}}

\item{all_but_reg}{logical value indicating which region attributes
you want to exclude; if FALSE, only the regions attributes specified in 
\emph{regions} argumentare kept in the output of the operation; if TRUE, 
the regions attributes are all kept except those in \emph{regions} argument.
If \emph{regions} is not defined, \emph{all_but_reg} is not considerd.}
}
\value{
GMQLDataset object. It contains the value to use as input 
for the subsequent GMQLDataset method
}
\description{
Wrapper to GMQL PROJECT operator

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 specified.
Region coordinates and values of the remaining metadata and/or region 
attributes remain equal to those in the input dataset. It allows to:
\itemize{
\item{Remove existing metadata and/or region attributes from a dataset}
\item{Update or set new metadata and/or region attributes in the result}
}
}
\examples{
## This statement initializes and runs the GMQL server for local execution 
## and creation of results on disk. Then, with system.file() it defines 
## the path to the folder "DATASET" in the subdirectory "example" 
## of the package "RGMQL" and opens such folder as a GMQL dataset 
## named "data"

init_gmql()
test_path <- system.file("example", "DATASET", package = "RGMQL")
data = read_gmql(test_path)

## This statement creates a new dataset called CTCF_NORM_SCORE by preserving 
## all region attributes apart from score, and creating a new region 
## attribute called new_score by dividing the existing score value of each 
## region by 1000.0 and incrementing it by 100.
## It also generates, for each sample of the new dataset, 
## a new metadata attribute called normalized with value 1, 
## which can be used in future selections.


CTCF_NORM_SCORE = select(data, metadata_update = list(normalized = 1), 
    regions_update = list(new_score = (score / 1000.0) + 100), 
    regions = c("score"), all_but_reg = TRUE)

}