Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/77193
Título: | UPIMAPI, reCOGnizer and KEGGCharter: bioinformatics tools for functional annotation and visualization of (meta)-omics datasets |
Autor(es): | Sequeira, J. C. Rocha, Miguel Alves, M. M. Salvador, Andreia Filipa Ferreira |
Palavras-chave: | Genomics Metagenomics Metatranscriptomics Functional annotation Metabolic pathways mapping Differential expression analysis |
Data: | 9-Abr-2022 |
Editora: | Elsevier |
Revista: | Computational and Structural Biotechnology Journal |
Citação: | Sequeira, J. C.; Rocha, Miguel; Alves, M. Madalena; Salvador, Andreia F., UPIMAPI, reCOGnizer and KEGGCharter: bioinformatics tools for functional annotation and visualization of (meta)-omics datasets. Computational and Structural Biotechnology Journal, 20, 1798-1810, 2022 |
Resumo(s): | Omics and meta-omics technologies are powerful approaches to explore microorganisms functions, but the sheer size and complexity of omics datasets often turn the analysis into a challenging task. Software developed for omics and meta-omics analyses, together with knowledgebases encompassing information on genes, proteins, taxonomic and functional annotation, among other types of information, are valuable resources for analyzing omics data. Although several bioinformatics resources are available for meta-omics analyses, many require significant computational expertise. Web interfaces are more user-friendly, but often struggle to handle large data files, such as those obtained in metagenomics, metatranscriptomics, or metaproteomics experiments. In this work, we present three novel bioinformatics tools, which are available through user-friendly command-line interfaces, can be run sequentially or stand-alone, and combine popular resources for functional annotation. UPIMAPI performs sequence homology-based annotation and obtains data from UniProtKB (e.g., protein names, EC numbers, Gene Ontology, Taxonomy, cross-references to external databases). reCOGnizer performs multithreaded domain homology-based annotation of protein sequences with several functional databases (i.e., CDD, NCBIfam, Pfam, Protein Clusters, SMART, TIGRFAM, COG and KOG) and in addition, obtains information on domain names and descriptions and EC numbers. KEGGCharter represents omics results, including differential gene expression, in KEGG metabolic pathways. In addition, it shows the taxonomic assignment of the enzymes represented, which is particularly useful in metagenomics studies in which several microorganisms are present. reCOGnizer, UPIMAPI and KEGGCharter together provide a comprehensive and complete functional characterization of large datasets, facilitating the interpretation of microbial activities in nature and in biotechnological processes. |
Tipo: | Artigo |
Descrição: | All the scripts and commands used in this paper are available at: https://github.com/iquasere/annotation_paper. The real dataset analysed in this paper was deposited in ENA database under the study accession PRJEB50269 (https://www.ebi.ac.uk/ena/browser/view/PRJEB50269). |
URI: | https://hdl.handle.net/1822/77193 |
DOI: | 10.1016/j.csbj.2022.03.042 |
ISSN: | 2001-0370 |
Versão da editora: | https://www.sciencedirect.com/journal/computational-and-structural-biotechnology-journal |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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document_55456_1.pdf Acesso restrito! | 2,17 MB | Adobe PDF | Ver/Abrir |