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https://hdl.handle.net/1822/56365
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Campo DC | Valor | Idioma |
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dc.contributor.author | Sequeira, J. C. | por |
dc.contributor.author | Rocha, Miguel | por |
dc.contributor.author | Alves, M. M. | por |
dc.contributor.author | Salvador, Andreia Filipa Ferreira | por |
dc.date.accessioned | 2018-10-18T14:25:25Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Sequeira, J. C.; Rocha, Miguel; Alves, M. Madalena; Salvador, Andreia F., MOSCA: an automated pipeline for integrated metagenomics and metatranscriptomics data analysis. Advances in Intelligent Systems and Computing. Vol. 803 (PACBB 2018), Springer, 183-191, 2019. | por |
dc.identifier.isbn | 9783319987019 | por |
dc.identifier.issn | 2194-5357 | por |
dc.identifier.uri | https://hdl.handle.net/1822/56365 | - |
dc.description.abstract | Metagenomics (MG) and Metatranscriptomics (MT) approaches open new perspectives on the interpretation of biological systems composed by complex microbial communities. Dealing with large sequencing datasets, to extract the desired information and interpret the results are big challenges associated with meta-omics studies. There are several bioinformatics pipelines for MG data analysis and less to MT. Up to date, none performs a complete analysis integrating both MG and MT data, including the assembly of reads into contigs, functional and taxonomic annotation of identified genes, differential gene expression analysis and the comparison of multiple samples. Here, we present Meta-Omics Software for Community Analysis (MOSCA) that was designed with this purpose. It integrates RNA-Seq analysis with Whole Genome Sequencing as reference. Raw sequencing reads are submitted to preprocessing for quality trimming and rRNA removal, and assembled into contigs, which afterwards are annotated by using a reference database. MOSCA performs differential gene expression and provides graphical visualization of the results and comparison of multiple samples. Validation and reproducibility of the pipeline was obtained by using simulated MG and MT datasets. | por |
dc.description.sponsorship | This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte, and by the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 323009. | por |
dc.language.iso | eng | por |
dc.publisher | Springer | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147337/PT | por |
dc.relation | info:eu-repo/grantAgreement/EC/FP7/323009/EU | por |
dc.rights | restrictedAccess | por |
dc.subject | Metagenomics | por |
dc.subject | Metatranscriptomics | por |
dc.subject | Bioinformatics pipeline | por |
dc.subject | Community analysis | por |
dc.subject | RNA-Seq | por |
dc.subject | Whole genome sequencing | por |
dc.title | MOSCA: an automated pipeline for integrated metagenomics and metatranscriptomics data analysis | por |
dc.type | conferencePaper | - |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | http://www.springer.com/series/11156 | por |
dc.comments | CEB48948 | por |
oaire.citationStartPage | 183 | por |
oaire.citationEndPage | 191 | por |
oaire.citationVolume | 803 | por |
dc.date.updated | 2018-10-18T10:04:13Z | - |
dc.identifier.eissn | 2194-5365 | por |
dc.identifier.doi | 10.1007/978-3-319-98702-6_22 | por |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Advances in Intelligent Systems and Computing | por |
sdum.conferencePublication | PRACTICAL APPLICATIONS OF COMPUTATIONAL BIOLOGY AND BIOINFORMATICS | por |
Aparece nas coleções: | CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series |
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document_48948_1.pdf Acesso restrito! | 1,94 MB | Adobe PDF | Ver/Abrir |