Software for Computing and Annotating Genomic Ranges

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Abstract

We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

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Most cited references 4

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Maintaining knowledge about temporal intervals

James Allen (1983)

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ShortRead: a bioconductor package for input, quality assessment and exploration of high-throughput sequence data

Martin Morgan, Simon Anders, Michael Lawrence … (2009)

Summary: ShortRead is a package for input, quality assessment, manipulation and output of high-throughput sequencing data. ShortRead is provided in the R and Bioconductor environments, allowing ready access to additional facilities for advanced statistical analysis, data transformation, visualization and integration with diverse genomic resources. Availability and Implementation: This package is implemented in R and available at the Bioconductor web site; the package contains a ‘vignette’ outlining typical work flows. Contact: mtmorgan@fhcrc.org

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Heritable individual-specific and allele-specific chromatin signatures in humans.

Ryan McDaniell, Bum-Kyu Lee, Lingyun Song … (2010)

The extent to which variation in chromatin structure and transcription factor binding may influence gene expression, and thus underlie or contribute to variation in phenotype, is unknown. To address this question, we cataloged both individual-to-individual variation and differences between homologous chromosomes within the same individual (allele-specific variation) in chromatin structure and transcription factor binding in lymphoblastoid cells derived from individuals of geographically diverse ancestry. Ten percent of active chromatin sites were individual-specific; a similar proportion were allele-specific. Both individual-specific and allele-specific sites were commonly transmitted from parent to child, which suggests that they are heritable features of the human genome. Our study shows that heritable chromatin status and transcription factor binding differ as a result of genetic variation and may underlie phenotypic variation in humans.