CompGO: an R package for comparing and visualizing gene ontology enrichment differences between DNA binding experiments
Waardenberg, Ashley J., Bassett, Samuel D., Bouveret, Romaric, and Harvey, Richard P. (2015) CompGO: an R package for comparing and visualizing gene ontology enrichment differences between DNA binding experiments. BMC Bioinformatics, 16. 275.
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Abstract
Background: Gene ontology (GO) enrichment is commonly used for inferring biological meaning from systems biology experiments. However, determining differential GO and pathway enrichment between DNA-binding experiments or using the GO structure to classify experiments has received little attention.
Results: Herein, we present a bioinformatics tool, CompGO, for identifying Differentially Enriched Gene Ontologies, called DiEGOs, and pathways, through the use of a z-score derivation of log odds ratios, and visualizing these differences at GO and pathway level. Through public experimental data focused on the cardiac transcription factor NKX2-5, we illustrate the problems associated with comparing GO enrichments between experiments using a simple overlap approach.
Conclusions: We have developed an R/Bioconductor package, CompGO, which implements a new statistic normally used in epidemiological studies for performing comparative GO analyses and visualizing comparisons from .BED data containing genomic coordinates as well as gene lists as inputs. We justify the statistic through inclusion of experimental data and compare to the commonly used overlap method. CompGO is freely available as a R/Bioconductor package enabling easy integration into existing pipelines and is available at: http://www.bioconductor.org/packages/release/bioc/html/CompGO.html packages/release/bioc/html/CompGO.html
| Item ID: | 55658 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 1471-2105 |
| Copyright Information: | Copyright © Waardenberg et al. 2016. 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. |
| Funders: | National Health and Medical Research Council (NHMRC), Australian Research Council (ARC) |
| Projects and Grants: | NHMRC Grant No. 573705, NHMRC Grant No. 573703, NHMRC Grant No. 1061539, ARC (Stem Cells Australia) 110001002, Australian-Indian Strategic Research Fund BF02008 |
| Date Deposited: | 25 Sep 2018 03:08 |
| FoR Codes: | 06 BIOLOGICAL SCIENCES > 0601 Biochemistry and Cell Biology > 060102 Bioinformatics @ 30% 08 INFORMATION AND COMPUTING SCIENCES > 0803 Computer Software > 080301 Bioinformatics Software @ 70% |
| SEO Codes: | 97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 100% |
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