aggregate: Method aggregate

In RGMQL: GenoMetric Query Language for R/Bioconductor

Description

Wrapper to GMQL MERGE operator

It builds a dataset consisting of a single sample having as many regions as the number of regions of all the input dataset samples and as many metadata as the union of the 'attribute-value' tuples of the input samples. If groupBy 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 metadata are not present in the grouping metadata parameter are disregarded.

Usage

## S4 method for signature 'GMQLDataset'
aggregate(x, groupBy = conds())

Arguments

x	GMQLDataset class object
groupBy	condition_evaluation function to support methods with groupBy or JoinBy input paramter

Value

GMQLDataset object. It contains the value to use as input for the subsequent GMQLDataset method

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 file as a GMQL dataset named "exp" 
## using CustomParser

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

## This statement creates a dataset called merged which contains one 
## sample for each antibody_target and cell value found within the metadata 
## of the exp dataset sample; each created sample contains all regions 
## from all 'exp' samples with a specific value for their 
## antibody_target and cell metadata attributes.

merged = aggregate(exp, conds(c("antibody_target", "cell")))

RGMQL documentation built on Nov. 8, 2020, 5:59 p.m.