M
Michael F. Lawrence
Researcher at Genentech
Publications - 9
Citations - 3425
Michael F. Lawrence is an academic researcher from Genentech. The author has contributed to research in topics: Bioconductor & Software. The author has an hindex of 7, co-authored 9 publications receiving 2526 citations. Previous affiliations of Michael F. Lawrence include Fred Hutchinson Cancer Research Center.
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Journal ArticleDOI
Software for computing and annotating genomic ranges.
Michael F. Lawrence,Wolfgang Huber,Hervé Pagès,Patrick Aboyoun,Marc R. J. Carlson,Robert Gentleman,Martin Morgan,Vincent J. Carey +7 more
TL;DR: This work describes Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions, including those for sequence analysis, differential expression analysis and visualization.
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VariantAnnotation: a Bioconductor package for exploration and annotation of genetic variants
Valerie Obenchain,Michael F. Lawrence,Vincent J. Carey,Stephanie M. Gogarten,Paul Shannon,Martin Morgan +5 more
TL;DR: VariantAnnotation allows ready access to additional R / Bioconductor facilities for advanced statistical analysis, data transformation, visualization and integration with diverse genomic resources.
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SeqArray-a storage-efficient high-performance data format for WGS variant calls.
Xiuwen Zheng,Stephanie M. Gogarten,Michael F. Lawrence,Adrienne M. Stilp,Matthew P. Conomos,Bruce S. Weir,Cathy C. Laurie,David K. Levine +7 more
TL;DR: A new WGS variant data format implemented in the R/Bioconductor package ‘SeqArray’ for storing variant calls in an array‐oriented manner which provides the same capabilities as VCF, but with multiple high compression options and data access using high‐performance parallel computing.
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Data structures and algorithms for analysis of genetics of gene expression with Bioconductor
TL;DR: This work is motivated by emerging requirements for data architectures and algorithm interfaces to allow flexible exploration of public and private archives of genotyping and expression arrays to allow interactively explored and analyzed using commodity hardware.
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Enhancing Reproducibility and Collaboration via Management of R Package Cohorts
TL;DR: This work introduces the package manifest as a central data structure for representing version specific, decentralized package cohorts and provides a high-level interface for creating and switching between side-by-side package libraries derived from manifests.