Affiliation:
1. Department of Biological Sciences, Kuwait University, 13060 Kuwait City, Kuwait
2. Institute of Health Policy Management and Evaluation, University of Toronto, Toronto M5T 1P8, Ontario, Canada
Abstract
Abstract
Summary
Having multiple datasets is a key aspect of robust bioinformatics analyses, because it allows researchers to find possible confirmation of the discoveries made on multiple cohorts. For this purpose, Gene Expression Omnibus (GEO) can be a useful database, since it provides hundreds of thousands of microarray gene expression datasets freely available for download and usage. Despite this large availability, collecting prognostic datasets of a specific cancer type from GEO can be a long, time-consuming and energy-consuming activity for any bioinformatician, who needs to execute it manually by first performing a search on the GEO website and then by checking all the datasets found one by one. To solve this problem, we present here geoCancerPrognosticDatasetsRetriever, a Perl 5 application which reads a cancer type and a list of microarray platforms, searches for prognostic gene expression datasets of that cancer type and based on those platforms available on GEO, and returns the GEO accession codes of those datasets, if found. Our bioinformatics tool can easily generate in a few minutes a list of cancer prognostic datasets that otherwise would require numerous hours of manual work to any bioinformatician. geoCancerPrognosticDatasetsRetriever can handily retrieve multiple prognostic datasets of gene expression of any cancer type, laying the foundations for numerous bioinformatics studies and meta-analyses that can have a strong impact on oncology research.
Availability and implementation
geoCancerPrognosticDatasetsRetriever is freely available under the GPLv2 license on the Comprehensive Perl Archive Network (CPAN) at https://metacpan.org/pod/App::geoCancerPrognosticDatasetsRetriever and on GitHub at https://github.com/AbbasAlameer/geoCancerPrognosticDatasetsRetriever.
Supplementary information
Supplementary data are available at Bioinformatics online.
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Cited by
21 articles.
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