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MiCId GUI: The Graphical User Interface for MiCId, a Fast Microorganism Classification and Identification Workflow with Accurate Statistics and High Recall.
Ogurtsov, Aleksey; Alves, Gelio; Rubio, Alex; Joyce, Brendan; Andersson, Björn; Karlsson, Roger; Moore, Edward R B; Yu, Yi-Kuo.
Afiliação
  • Ogurtsov A; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
  • Alves G; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
  • Rubio A; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
  • Joyce B; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
  • Andersson B; Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Karlsson R; Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Moore ERB; Nanoxis Consulting AB, Gothenburg, Sweden.
  • Yu YK; Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
J Comput Biol ; 31(2): 175-178, 2024 02.
Article em En | MEDLINE | ID: mdl-38301204
ABSTRACT
Although many user-friendly workflows exist for identifications of peptides and proteins in mass-spectrometry-based proteomics, there is a need of easy to use, fast, and accurate workflows for identifications of microorganisms, antimicrobial resistant proteins, and biomass estimation. Identification of microorganisms is a computationally demanding task that requires querying thousands of MS/MS spectra in a database containing thousands to tens of thousands of microorganisms. Existing software can't handle such a task in a time efficient manner, taking hours to process a single MS/MS experiment. Another paramount factor to consider is the necessity of accurate statistical significance to properly control the proportion of false discoveries among the identified microorganisms, and antimicrobial-resistant proteins, and to provide robust biomass estimation. Recently, we have developed Microorganism Classification and Identification (MiCId) workflow that assigns accurate statistical significance to identified microorganisms, antimicrobial-resistant proteins, and biomass estimation. MiCId's workflow is also computationally efficient, taking about 6-17 minutes to process a tandem mass-spectrometry (MS/MS) experiment using computer resources that are available in most laptop and desktop computers, making it a portable workflow. To make data analysis accessible to a broader range of users, beyond users familiar with the Linux environment, we have developed a graphical user interface (GUI) for MiCId's workflow. The GUI brings to users all the functionality of MiCId's workflow in a friendly interface along with tools for data analysis, visualization, and to export results.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Espectrometria de Massas em Tandem / Anti-Infecciosos Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: J Comput Biol Assunto da revista: BIOLOGIA MOLECULAR / INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Espectrometria de Massas em Tandem / Anti-Infecciosos Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: J Comput Biol Assunto da revista: BIOLOGIA MOLECULAR / INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos