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Visualizing metagenomic and metatranscriptomic data: A comprehensive review

Journal Article · · Computational and Structural Biotechnology Journal
 [1];  [2];  [1];  [2];  [2];  [1];  [3];  [4];  [5];  [6];  [7];  [8];  [2]
  1. Alexander Fleming Biomedical Sciences Research Center (BSRC), Vari (Greece). Institute for Fundamental Biomedical Research; Univ. of Athens (Greece)
  2. Alexander Fleming Biomedical Sciences Research Center (BSRC), Vari (Greece). Institute for Fundamental Biomedical Research
  3. Univ. of Crete, Heraklion (Greece)
  4. Alexander Fleming Biomedical Sciences Research Center (BSRC), Vari (Greece). Institute for Fundamental Biomedical Research; European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge (United Kingdom). European Bioinformatics Institute (EBI)
  5. Hellenic Centre for Marine Research (HCMR), Heraklion (Greece). Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC)
  6. Pennsylvania State Univ., Hershey, PA (United States). College of Medicine
  7. USDOE Joint Genome Institute (JGI), Berkeley, CA (United States)
  8. Alexander Fleming Biomedical Sciences Research Center (BSRC), Vari (Greece). Institute for Fundamental Biomedical Research; Pennsylvania State Univ., Hershey, PA (United States). College of Medicine; National and Kapodistrian Univ. of Athens (Greece); Hellenic Army Academy, Vari (Greece)

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
2447710
Journal Information:
Computational and Structural Biotechnology Journal, Journal Name: Computational and Structural Biotechnology Journal Vol. 23; ISSN 2001-0370
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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