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Published September 13, 2016 | Published + Supplemental Material
Journal Article Open

Tissue enrichment analysis for C. elegans genomics

Abstract

Background: Over the last ten years, there has been explosive development in methods for measuring gene expression. These methods can identify thousands of genes altered between conditions, but understanding these datasets and forming hypotheses based on them remains challenging. One way to analyze these datasets is to associate ontologies (hierarchical, descriptive vocabularies with controlled relations between terms) with genes and to look for enrichment of specific terms. Although Gene Ontology (GO) is available for Caenorhabditis elegans, it does not include anatomical information. Results: We have developed a tool for identifying enrichment of C. elegans tissues among gene sets and generated a website GUI where users can access this tool. Since a common drawback to ontology enrichment analyses is its verbosity, we developed a very simple filtering algorithm to reduce the ontology size by an order of magnitude. We adjusted these filters and validated our tool using a set of 30 gold standards from Expression Cluster data in WormBase. We show our tool can even discriminate between embryonic and larval tissues and can even identify tissues down to the single-cell level. We used our tool to identify multiple neuronal tissues that are down-regulated due to pathogen infection in C. elegans. Conclusions: Our Tissue Enrichment Analysis (TEA) can be found within WormBase, and can be downloaded using Python's standard pip installer. It tests a slimmed-down C. elegans tissue ontology for enrichment of specific terms and provides users with a text and graphic representation of the results.

Additional Information

© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Received: 30 April 2016; Accepted: 26 August 2016; Published online: 13 September 2016. We thank Justin Bois for his help and support. We would like to acknowledge all members of the Sternberg lab for helpful discussion. This work was supported by HG002223 from the National Human Genome Research Institute to PWS., and H.H.M.I., with which PWS is an investigator. The funding agencies had no input into the design, execution or interpretation of our experiments, nor into the writing of this manuscript. Availability of data and materials: Our web implementation is available at http://www.wormbase.org/tools/enrichment/tea/tea.cgi. Our software can also be downloaded using Python's pip installer via the command pip install tissue_enrichment_analysis Alternatively, our software is available for download at: http://dangeles.github.io/TissueEnrichmentAnalysis All benchmark gene sets, benchmarking code and Figures can also be found at the same address, under the 'tests' folder. Authors' contributions: DA and PWS conceived of the project; DA developed algorithm; RYL made intellectual contributions to the project; RYL and JC developed the web GUI. All authors read and approved the final manuscript. The authors declare that they have no competing interests. Consent for publication: Not applicable. Ethics approval and consent to participate: Not applicable.

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Created:
August 20, 2023
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