Motivation: Analysis of genomic sequencing data requires efficient, easy-to-use access to alignment results and flexible data management tools (e.g. filtering, merging, sorting, etc.). However, the enormous amount of data produced by current sequencing technologies is typically stored in compressed, binary formats that are not easily handled by the text-based parsers commonly used in bioinformatics research.
Results: We introduce a software suite for programmers and end users that facilitates research analysis and data management using BAM files. BamTools provides both the first C++ API publicly available for BAM file support as well as a command-line toolkit.
Availability: BamTools was written in C++, and is supported on Linux, Mac OSX and MS Windows. Source code and documentation are freely available at http://github.org/pezmaster31/bamtools.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3106182 | PMC |
http://dx.doi.org/10.1093/bioinformatics/btr174 | DOI Listing |
Bioinformatics
July 2013
Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany.
Motivation: Protocols to generate strand-specific transcriptomes with next-generation sequencing platforms have been used by the scientific community roughly since 2008. Strand-specific reads allow for detection of antisense events and a higher resolution of expression profiles enabling extension of current transcript annotations. However, applications making use of this strandedness information are still scarce.
View Article and Find Full Text PDFBioinformatics
June 2011
Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.
Motivation: Analysis of genomic sequencing data requires efficient, easy-to-use access to alignment results and flexible data management tools (e.g. filtering, merging, sorting, etc.
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