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Novel Bioinformatics Tools for Omics Data Analysis and Visualization
Author(s) -
Karp Peter D,
Paley Suzanne,
Billington Richard
Publication year - 2018
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2018.32.1_supplement.lb120
Subject(s) - computational biology , dashboard , visualization , computer science , data visualization , bioinformatics , biology , data mining , data science
We describe several novel software tools for analysis of gene expression, proteomic, and metabolomics data. The tools are integrated with the HumanCyc.org database and website that integrates the human genome with knowledge of human metabolism. HumanCyc is curated from the biomedical literature and describes 314 human metabolic pathways, 2887 human metabolic reactions, and 1929 human metabolites. These same tools are also available via the BioCyc.org website, which contains 10,980 genomes. The Omics Dashboard enables interactive exploration and analysis of gene‐expression and metabolomics datasets. The dashboard presents a visual read‐out of the expression status of many cellular systems to facilitate a rapid visual survey of the responses of cellular systems to a given stimulus. The Dashboard also enables the user to quickly find and understand the responses of genes or metabolites within one or more specific systems of interest. The dashboard is organized as a hierarchy of cellular systems. At its highest level the dashboard contains graphical panels for cellular systems such as biosynthesis, energy metabolism, and regulation. Each of those panels contains a series of X‐Y plots depicting the expression levels of genes within subsystems of that panel. For example, subsystems within the central dogma panel include transcription, translation, and DNA metabolism. Clicking on a plot such as DNA metabolism yields plots for its subsystems such as DNA replication and DNA repair. Eventually this drill‐down process leads to plots of expression levels for all of the individual genes within a subsystem. Within the dashboard the user can also paint expression data on pathway diagrams. The dashboard can compute enrichment scores for each subsystem and is complementary to traditional statistical methods for analysis of gene‐expression data. A second set of tools enable omics data analysis in a metabolic pathway context. For example, gene expression and metabolomics data can be painted onto a zoomable metabolic map diagram for an organism's metabolic network to enable visualization of the activity levels of all metabolic pathways. Users can also create personalized multi‐pathway diagrams called pathway collages that combine a user‐selected set of interconnected metabolic pathways and can be painted with omics data. In addition, individual pathway diagrams can be painted with omics data. Support or Funding Information This work was funded by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number GM075742 to P.D.K. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.Omics Dashboard showing a human metabolomics dataset comparing metabolomics measurements for subcutaneous versus visceral adipose tissue. The first level of the Dashboard shows metabolites across many human metabolic pathways; the TCA cycle shows differences in metabolite response, so the user has requested the diagram on the right, which graphs the levels of all TCA cycle metabolites.Escherichia coli metabolic network diagram painted with transcriptomics data. Orange and red highlighting indicate highly expressed genes, blue and purple indicate genes with low expression.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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