Orchestrating high-throughput genomic analysis with Bioconductor
Wolfgang Huber,Vincent J. Carey,Robert Gentleman,Simon Anders,Marc R. J. Carlson,Benilton S. Carvalho,Héctor Corrada Bravo,Sean Davis,Laurent Gatto,Thomas Girke,Raphael Gottardo,Florian Hahne,Kasper D. Hansen,Rafael A. Irizarry,Michael S. Lawrence,Michael I. Love,James W. MacDonald,Valerie Obenchain,Andrzej K. Oleś,Hervé Pagès,Alejandro Reyes,Paul Shannon,Gordon K. Smyth,Dan Tenenbaum,Levi Waldron,Martin Morgan +25 more
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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.Abstract:
Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors.read more
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Current best practices in single-cell RNA-seq analysis: a tutorial.
Malte D Luecken,Fabian J. Theis +1 more
TL;DR: The steps of a typical single‐cell RNA‐seq analysis, including pre‐processing (quality control, normalization, data correction, feature selection, and dimensionality reduction) and cell‐ and gene‐level downstream analysis, are detailed.
Journal ArticleDOI
A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor
TL;DR: This article describes a computational workflow for low-level analyses of scRNA-seq data, based primarily on software packages from the open-source Bioconductor project, which covers basic steps including quality control, data exploration and normalization, as well as more complex procedures such as cell cycle phase assignment.
Journal ArticleDOI
Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R.
TL;DR: The R/Bioconductor package scater is developed to facilitate rigorous pre‐processing, quality control, normalization and visualization of scRNA‐seq data and provides a convenient, flexible workflow to process raw sequencing reads into a high‐quality expression dataset ready for downstream analysis.
Journal ArticleDOI
ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization
TL;DR: Reactome is a manually curated pathway annotation database for unveiling high-order biological pathways from high-throughput data and ReactomePA is an R/Bioconductor package providing enrichment analyses, including hypergeometric test and gene set enrichment analyses.
Journal ArticleDOI
Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences.
TL;DR: The proposed method, Approximate Posterior Estimation for generalized linear model, apeglm, has lower bias than previously proposed shrinkage estimators, while still reducing variance for those genes with little information for statistical inference.
References
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The Sequence Alignment/Map format and SAMtools
Heng Li,Bob Handsaker,Alec Wysoker,T. J. Fennell,Jue Ruan,Nils Homer,Gabor T. Marth,Gonçalo R. Abecasis,Richard Durbin +8 more
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An integrated encyclopedia of DNA elements in the human genome
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Differential expression analysis for sequence count data.
Simon Anders,Wolfgang Huber +1 more
TL;DR: A method based on the negative binomial distribution, with variance and mean linked by local regression, is proposed and an implementation, DESeq, as an R/Bioconductor package is presented.
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Bioconductor: open software development for computational biology and bioinformatics
Robert Gentleman,Vincent J. Carey,Douglas M. Bates,Benjamin M. Bolstad,Marcel Dettling,Sandrine Dudoit,Byron Ellis,Laurent Gautier,Yongchao Ge,Jeff Gentry,Kurt Hornik,Torsten Hothorn,Wolfgang Huber,Stefano Maria Iacus,Rafael A. Irizarry,Friedrich Leisch,Cheng Li,Martin Maechler,A. J. Rossini,Günther Sawitzki,Colin A. Smith,Gordon K. Smyth,Luke Tierney,Jean Yang,Jianhua Zhang +24 more
TL;DR: Details of the aims and methods of Bioconductor, the collaborative creation of extensible software for computational biology and bioinformatics, and current challenges are described.
Journal ArticleDOI
Minimum information about a microarray experiment (MIAME)-toward standards for microarray data.
Alvis Brazma,Pascal Hingamp,John Quackenbush,Gavin Sherlock,Paul T. Spellman,Chris Stoeckert,John Aach,Wilhelm Ansorge,Catherine A. Ball,Helen C. Causton,Terry Gaasterland,Patrick Glenisson,Frank C. P. Holstege,Irene F. Kim,Victor Markowitz,John C. Matese,Helen Parkinson,Alan J. Robinson,Ugis Sarkans,Steffen Schulze-Kremer,Jason E. Stewart,Ronald C. Taylor,Jaak Vilo,Martin Vingron +23 more
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