3 research outputs found

    BAMQL: a query language for extracting reads from BAM files

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    Abstract Background It is extremely common to need to select a subset of reads from a BAM file based on their specific properties. Typically, a user unpacks the BAM file to a text stream using SAMtools, parses and filters the lines using AWK, then repacks them using SAMtools. This process is tedious and error-prone. In particular, when working with many columns of data, mix-ups are common and the bit field containing the flags is unintuitive. There are several libraries for reading BAM files, such as Bio-SamTools for Perl and pysam for Python. Both allow access to the BAM’s read information and can filter reads, but require substantial boilerplate code; this is high overhead for mostly ad hoc filtering. Results We have created a query language that gathers reads using a collection of predicates and common logical connectives. Queries run faster than equivalents and can be compiled to native code for embedding in larger programs. Conclusions BAMQL provides a user-friendly, powerful and performant way to extract subsets of BAM files for ad hoc analyses or integration into applications. The query language provides a collection of predicates beyond those in SAMtools, and more flexible connectives

    BAMQL:A query language for extracting reads from BAM files

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    BACKGROUND: It is extremely common to need to select a subset of reads from a BAM file based on their specific properties. Typically, a user unpacks the BAM file to a text stream using SAMtools, parses and filters the lines using AWK, then repacks them using SAMtools. This process is tedious and error-prone. In particular, when working with many columns of data, mix-ups are common and the bit field containing the flags is unintuitive. There are several libraries for reading BAM files, such as Bio-SamTools for Perl and pysam for Python. Both allow access to the BAM’s read information and can filter reads, but require substantial boilerplate code; this is high overhead for mostly ad hoc filtering. RESULTS: We have created a query language that gathers reads using a collection of predicates and common logical connectives. Queries run faster than equivalents and can be compiled to native code for embedding in larger programs. CONCLUSIONS: BAMQL provides a user-friendly, powerful and performant way to extract subsets of BAM files for ad hoc analyses or integration into applications. The query language provides a collection of predicates beyond those in SAMtools, and more flexible connectives. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1162-y) contains supplementary material, which is available to authorized users
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