take {RGMQL} | R Documentation |
Wrapper to TAKE operation
It saves the content of a dataset that contains samples metadata and regions as GRangesList. It is normally used to store in memory the content of any dataset generated during a GMQL query. The operation can be very time-consuming. If you invoked any materialization before take function, all those datasets are materialized as folders.
take(.data, ...) ## S4 method for signature 'GMQLDataset' take(.data, rows = 0L)
.data |
returned object from any GMQL function |
... |
Additional arguments for use in other specific methods of the generic take function |
rows |
number of regions rows for each sample that you want to retrieve and store in memory. By default it is 0, that means take all rows for each sample |
GRangesList with associated metadata
## 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 "rd" using CustomParser init_gmql() test_path <- system.file("example", "DATASET", package = "RGMQL") rd = read_gmql(test_path) ## This statement creates a dataset called 'aggr' which contains one ## sample for each antibody_target and cell value found within the metadata ## of the 'rd' dataset sample; each created sample contains all regions ## from all 'rd' samples with a specific value for their ## antibody_target and cell metadata attributes. aggr = aggregate(rd, conds(c("antibody_target", "cell"))) ## This statement performs the query and returns the resulted dataset as ## GRangesList named 'taken'. It returns only the first 45 regions of ## each sample present into GRangesList and all the medatata associated ## with each sample taken <- take(aggr, rows = 45)