PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data

Abstract The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental in better understanding interconnections across molecular layers and in fully utilizing the multi-omic resources available to make biological di...

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Published inNucleic acids research Vol. 46; no. W1; pp. W503 - W509
Main Authors Hernández-de-Diego, Rafael, Tarazona, Sonia, Martínez-Mira, Carlos, Balzano-Nogueira, Leandro, Furió-Tarí, Pedro, Pappas, Georgios J, Conesa, Ana
Format Journal Article
LanguageEnglish
Published England Oxford University Press 02.07.2018
Subjects
Cell Line, Transformed
Cellular Reprogramming
Computer Graphics
Fibroblasts - cytology
Fibroblasts - metabolism
Gene Expression Regulation
Genomics - methods
Humans
Internet
Metabolic Networks and Pathways - genetics
Metabolomics - methods
Molecular Sequence Annotation
Proteomics - methods
Signal Transduction - genetics
Software
Transcriptome
Web Server Issue
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Summary:Abstract The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental in better understanding interconnections across molecular layers and in fully utilizing the multi-omic resources available to make biological discoveries. We present here PaintOmics 3, a web-based resource for the integrated visualization of multiple omic data types onto KEGG pathway diagrams. PaintOmics 3 combines server-end capabilities for data analysis with the potential of modern web resources for data visualization, providing researchers with a powerful framework for interactive exploration of their multi-omics information. Unlike other visualization tools, PaintOmics 3 covers a comprehensive pathway analysis workflow, including automatic feature name/identifier conversion, multi-layered feature matching, pathway enrichment, network analysis, interactive heatmaps, trend charts, and more. It accepts a wide variety of omic types, including transcriptomics, proteomics and metabolomics, as well as region-based approaches such as ATAC-seq or ChIP-seq data. The tool is freely available at www.paintomics.org
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The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.
ISSN:0305-1048
1362-4962
DOI:10.1093/nar/gky466