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Bioconductor: open software development for computational biology and bioinformatics
TLDR
Details of the aims and methods of Bioconductor, the collaborative creation of extensible software for computational biology and bioinformatics, and current challenges are described.
Mixed-Effects Models in S and S-Plus
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Orchestrating high-throughput genomic analysis with Bioconductor
TLDR
An overview of Bioconductor, an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology, which comprises 934 interoperable packages contributed by a large, diverse community of scientists.
Software for Computing and Annotating Genomic Ranges
TLDR
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.
rtracklayer: an R package for interfacing with genome browsers
Summary: The rtracklayer package supports the integration of existing genome browsers with experimental data analyses performed in R. The user may (i) transfer annotation tracks to and from a genome
Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health)
TLDR
Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
VariantAnnotation: a Bioconductor package for exploration and annotation of genetic variants
TLDR
VariantAnnotation allows ready access to additional R / Bioconductor facilities for advanced statistical analysis, data transformation, visualization and integration with diverse genomic resources.
Machine Learning and Its Applications to Biology
TLDR
This tutorial discusses the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data in the field of supervised learning in R, the open source data analysis and visualization language.
Orchestrating single-cell analysis with Bioconductor
TLDR
An overview of single-cell RNA sequencing analysis for prospective users and contributors is presented, highlighting the contributions towards this effort made by Bioconductor.
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