getDataset: Get dataset in ExpressionSet format

Description

Get dataset for a given dataset identifier and platform identifier in a specific format.

Usage

getDataset(dataset, platform, ...);

Arguments

dataset

Valid dataset identifier: the GEO or InSilico DB accession code.

platform

The platform of the chip on which a measurement was done. A platform is identified by its GEO accession code.

...

Optional arguments can be passed to the function for more specific requests:

format = "CURESET"

File format in which the dataset should be returned. Possible values:

CURESET : Curated R/Bioconductor ExpressionSet.
ESET : R/Bioconductor ExpressionSet without curation.

features = "PROBE"

Type of features in which data is represented. Two possible values: "GENE" or "PROBE". By default an expression matrix containing probes is returned.

norm = "ORIGINAL"

Type of normalization to use when pre-processing a dataset. Possible normalizations: "ORIGINAL", "FRMA"[1], "SCAN"[2].

curation

Specific curation used to annotate a dataset. A curation is identified by a InSilico DB Curation identifier. You can annotate datasets yourself at https://insilicodb.com/app/browse If not defined, the prefered curation of specified dataset will be used.

timeout = 120

Time (in seconds) to wait for the dataset, if it has to be generated.

Value

A Bioconductors ExpressionSet.

References

[1] MN. McCall, BM. Bolstad, and RA. Irizarry, Frozen Robust Multi-Array Analysis (fRMA), Biostatistics, vol. 11, no. 2, pp. 242-253 , 2008. [2] SR. Piccolo, Y. Sun, JD. Campbell, ME. Lenburg, AH. Bild, and WE. Johnson, A single-sample microarray normalization method to facilitate personalized-medicine workflows, Genomics, vol. 100, no. 6, pp. 337-344, 2012.

Examples

Run this code

InSilicoLogin("rpackage_tester@insilicodb.com", "5c4d0b231e5cba4a0bc54783b385cc9a");
dataset.id <- "GSE4635";
platform.id <- getPlatforms(dataset.id);
eset <- getDataset(dataset.id, platform.id[[1]],
                   norm = "ORIGINAL", features = "PROBE");
print(dim(eset));
## Features  Samples 
##    22215        8 
eset <- getDataset( dataset.id, platform.id[[1]],
                   norm = "ORIGINAL", features = "GENE");
print(dim(eset));
## Features  Samples 
##    12698        8