CORaL: comparison of ranked lists for analysis of gene expression data.
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ABSTRACT:
SUBMITTER: Antosh M
PROVIDER: S-EPMC3667425 | biostudies-literature | 2013 Jun
REPOSITORIES: biostudies-literature
Publications
CORaL: comparison of ranked lists for analysis of gene expression data.
Antosh Michael M Fox David D Cooper Leon N LN Neretti Nicola N
Journal of computational biology : a journal of computational molecular cell biology 20130515 6
Because a very large number of gene expression data sets are currently publicly available, comparisons across experiments between different laboratories have become a common task. However, most existing methods of comparing gene expression data sets require setting arbitrary cutoffs (e.g., for statistical significance or fold change), which could select genes according to different criteria because of differences in experimental protocols and statistical analysis in different data sets. A new me ...[more]
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Project description:BackgroundGene expression profiling is a widely adopted method in areas like drug development or functional gene analysis. Microarray data of gene expression experiments is still commonly used and widely available for retrospective analyses. However, due to to changes of the underlying technologies data sets from different technologies are often difficult to compare and thus a multitude of already available data becomes difficult to use. We present a web application that abstracts away mathematical and programmatical details in order to enable a convenient and customizable analysis of microarray data for large-scale reproducibility studies. In addition, the web application provides a feature that allows easy access to large microarray repositories.ResultsOur web application consists of three basic steps which are necessary for a differential gene expression analysis as well as Gene Ontology (GO) enrichment analysis and the comparison of multiple analysis results. Genealyzer can handle Affymetrix data as well as one-channel and two-channel Agilent data. All steps are visualized with meaningful plots. The application offers flexible analysis while being intuitively operable.ConclusionsOur web application provides a unified platform for analysing microarray data, while allowing users to compare the results of different technologies and organisms. Beyond reproducibility, this also offers many possibilities for gaining further insights from existing study data, especially since data from different technologies or organisms can also be compared. The web application can be accessed via this URL: https://genealyzer.item.fraunhofer.de/ . Login credentials can be found at the end.
| S-EPMC10111666 | biostudies-literature