Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) web-server
Proietti, Carla, Zakrzewski , Martha , Watkins, Thomas S., Berger, Bernard, Hasan, Shihab, Ratnatunga, Champa N., Brion, Marie-Jo, Crompton, Peter D., Miles, John J., Doolan, Denise L., and Krause, Lutz (2016) Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) web-server. Scientific Reports, 6. 38178. pp. 1-15.
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Abstract
Genomics Data Miner (GMine) is a user-friendly online software that allows non-experts to mine, cluster and compare multidimensional biomolecular datasets. Various powerful visualization techniques are provided, generating high quality figures that can be directly incorporated into scientific publications. Robust and comprehensive analyses are provided via a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering and multivariable regression. The software has a focus on multivariate techniques, which can attribute variance in the measurements to multiple explanatory variables and confounders. Various normalization methods are provided. Extensive help pages and a tutorial are available via a wiki server. Using GMine we reanalyzed proteome microarray data of host antibody response against Plasmodium falciparum. Our results support the hypothesis that immunity to malaria is a higher-order phenomenon related to a pattern of responses and not attributable to any single antigen. We also analyzed gene expression across resting and activated T cells, identifying many immune-related genes with differential expression. This highlights both the plasticity of T cells and the operation of a hardwired activation program. These application examples demonstrate that GMine facilitates an accurate and in-depth analysis of complex molecular datasets, including genomics, transcriptomics and proteomics data.
| Item ID: | 46631 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 2045-2322 |
| Additional Information: | © The Author(s) 2016. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Funders: | Australian Government, National Health and Medical Research Council (NHMRC), Perpetual, National Institute of Allergy and Infectious Disease (NIAID) |
| Projects and Grants: | NHMRC PP1069281 & APP1078987, Perpetual FR2013/0946 |
| Date Deposited: | 14 Dec 2016 04:20 |
| FoR Codes: | 42 HEALTH SCIENCES > 4206 Public health > 420699 Public health not elsewhere classified @ 50% 32 BIOMEDICAL AND CLINICAL SCIENCES > 3204 Immunology > 320404 Cellular immunology @ 25% 32 BIOMEDICAL AND CLINICAL SCIENCES > 3204 Immunology > 320405 Humoural immunology and immunochemistry @ 25% |
| SEO Codes: | 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 100% |
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