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COnTORT: COmprehensive Transcriptomic ORganizational Tool for Simultaneously Retrieving and Organizing Numerous Gene
Kevin S Myers1, Michael Place1, Daniel R Noguera1,2
1Wisconsin Energy Institute and Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Microbiology Resource Announcements
|June 20, 2020
Summary
A new tool called COnTORT (Comprehensive Transcriptomic Organizational Tool) retrieves gene expression data from NCBI GEO. This program compiles essential transcriptomic data for bioinformatic analysis.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Gene expression data is crucial for understanding biological processes.
- Accessing and organizing transcriptomic data from public repositories can be challenging.
- The National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) is a major repository for such data.
Purpose of the Study:
- To introduce COnTORT (Comprehensive Transcriptomic Organizational Tool), a novel software solution.
- To automate the retrieval of comprehensive gene expression data and associated metadata from the NCBI GEO database.
- To facilitate downstream bioinformatic applications by providing organized data files.
Main Methods:
- Development of a publicly available software program named COnTORT.
- Implementation of data retrieval mechanisms to access the NCBI GEO database.
- Compilation of retrieved gene expression data and metadata into accessible text file formats.
Main Results:
- COnTORT successfully retrieves all available gene expression data for a specified organism from NCBI GEO.
- Associated metadata is systematically collected alongside the expression data.
- The output is organized into user-friendly text files, ready for further analysis.
Conclusions:
- COnTORT provides an efficient and comprehensive solution for accessing and organizing transcriptomic data.
- The tool simplifies the process of preparing data for various bioinformatic analyses.
- COnTORT enhances the accessibility and usability of public gene expression datasets.
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