David J Degnan, Daniel M Claborne, Rachel E Richardson, Clayton W Strauch, Evan C Glasscock, Dusan Veličković, Kristin E Burnum-Johnson, Bobbie-Jo M Webb-Robertson, Kelly G Stratton, Lisa M Bramer
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MODE: A Web Application for Interactive Visualization and Exploration of Omics Data.
Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as "omics") data allow researchers to find biomarkers or molecular targets or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data are multidimensional, and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries do not allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to sort and filter plots by categorical or numerical variables called metas. MODE allows users to build and share these displays with several options for plot design and meta selection. The MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".