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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Rqc: A Bioconductor Package for Quality Control of High-Throughput Sequencing Data

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de Souza, Welliton [1] ; Carvalho, Benilton de Sa [1] ; Lopes-Cendes, Iscia [2, 3]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Estadual Campinas, Campinas, SP - Brazil
[2] Univ Estadual Campinas, Sch Med Sci, Dept Med Genet, Campinas, SP - Brazil
[3] Univ Estadual Campinas, Brazilian Inst Neurosci & Neurotechnol BRAINN, Campinas, SP - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: JOURNAL OF STATISTICAL SOFTWARE; v. 87, n. CN2, p. 1-14, NOV 2018.
Citações Web of Science: 0

As sequencing costs drop with the constant improvements in the field, next-generation sequencing becomes one of the most used technologies in biological research. Sequencing technology allows the detailed characterization of events at the molecular level, including gene expression, genomic sequence and structural variants. Such experiments result in billions of sequenced nucleotides and each one of them is associated to a quality score. Several software tools allow the quality assessment of whole experiments. However, users need to switch between software environments to perform all steps of data analysis, adding an extra layer of complexity to the data analysis workflow. We developed Rqc, a Bioconductor package designed to assist the analyst during assessment of high-throughput sequencing data quality. The package uses parallel computing strategies to optimize large data sets processing, regardless of the sequencing platform. We created new data quality visualization strategies by using established analytical procedures. That improves the ability of identifying patterns that may affect downstream procedures, including undesired sources technical variability. The software provides a framework for writing customized reports that integrates seamlessly to the R/Bioconductor environment, including publication-ready images. The package also offers an interactive tool to generate quality reports dynamically. Rqc is implemented in R and it is freely available through the Bioconductor project (https://bioconductor.org/packages/Rqc/) for Windows, Linux and Mac OS X operating systems. (AU)

Processo FAPESP: 13/24801-2 - Análise e desenvolvimento de protocolos em bioinformática para estudos de epigenética
Beneficiário:Wélliton de Souza
Linha de fomento: Bolsas no Brasil - Mestrado