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fastQ_brew: module for analysis, preprocessing, and reformatting of FASTQ sequence data

BACKGROUND: Next generation sequencing datasets are stored as FASTQ formatted files. In order to avoid downstream artefacts, it is critical to implement a robust preprocessing protocol of the FASTQ sequence in order to determine the integrity and quality of the data. RESULTS: Here I describe fastQ_b...

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Detalles Bibliográficos
Autor principal: O’Halloran, Damien M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5508660/
https://www.ncbi.nlm.nih.gov/pubmed/28701181
http://dx.doi.org/10.1186/s13104-017-2616-7
Descripción
Sumario:BACKGROUND: Next generation sequencing datasets are stored as FASTQ formatted files. In order to avoid downstream artefacts, it is critical to implement a robust preprocessing protocol of the FASTQ sequence in order to determine the integrity and quality of the data. RESULTS: Here I describe fastQ_brew which is a package that provides a suite of methods to evaluate sequence data in FASTQ format and efficiently implements a variety of manipulations to filter sequence data by size, quality and/or sequence. fastQ_brew allows for mismatch searches to adapter sequences, left and right end trimming, removal of duplicate reads, as well as reads containing non-designated bases. fastQ_brew also returns summary statistics on the unfiltered and filtered FASTQ data, and offers FASTQ to FASTA conversion as well as FASTQ reverse complement and DNA to RNA manipulations. CONCLUSIONS: fastQ_brew is open source and freely available to all users at the following webpage: https://github.com/dohalloran/fastQ_brew.