ARGEOS

ARGEOS performs systematic searches and retrieval of microarray, RNA-seq, methylation, and CHIP-seq datasets from Gene Expression Omnibus (GEO) and ArrayExpress to support secondary transcriptome and genomic analyses.


Key Features:

  • Systematic search across GEO and ArrayExpress: Queries Gene Expression Omnibus (GEO) and ArrayExpress to collect unique datasets relevant to specific research queries.
  • Concurrent request handling: Supports submission and simultaneous processing of multiple search requests.
  • Modifiable search requests: Allows modification of submitted search requests to refine dataset retrieval.
  • Dataset metadata extraction: Retrieves detailed dataset information including experimental protocols, dataset counts, and raw data availability.
  • Support for multiple data types: Targets microarray, RNA-seq, methylation profiles, and CHIP-seq datasets.
  • Structured output format: Produces output formatted to minimize additional information processing for downstream analysis.

Scientific Applications:

  • Secondary transcriptome and genomic analyses: Enables reanalysis and validation of existing microarray and RNA-seq datasets to generate new insights or corroborate findings.
  • Studies of cell polarization and intracellular signaling: Facilitates systematic retrieval of transcriptome datasets related to activated/polarized cells triggered by immune stimuli.

Methodology:

Performs systematic searches across GEO and ArrayExpress, supports concurrent submission and modification of multiple search requests, retrieves dataset metadata (experimental protocols, dataset/sample counts, raw data availability), and outputs structured results for microarray, RNA-seq, methylation, and CHIP-seq datasets.

Topics

Details

Tool Type:
web application
Programming Languages:
Python
Added:
3/28/2022
Last Updated:
3/28/2022

Operations

Publications

Gavrish GE, Chistyakov DV, Sergeeva MG. ARGEOS: A New Bioinformatic Tool for Detailed Systematics Search in GEO and ArrayExpress. Biology. 2021;10(10):1026. doi:10.3390/biology10101026. PMID:34681124. PMCID:PMC8533512.

PMID: 34681124
PMCID: PMC8533512
Funding: - Russian Foundation for Basic Research: 19-29-01243

Links