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.
CITATION STYLE
O’Halloran, D. M. (2017). FastQ-brew: Module for analysis, preprocessing, and reformatting of FASTQ sequence data. BMC Research Notes, 10(1). https://doi.org/10.1186/s13104-017-2616-7
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