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.
Description
Orchestrating high-throughput genomic analysis with Bioconductor. - PubMed - NCBI
%0 Journal Article
%1 Huber:2015:Nat-Methods:25633503
%A Huber, W
%A Carey, V J
%A Gentleman, R
%A Anders, S
%A Carlson, M
%A Carvalho, B S
%A Bravo, H C
%A Davis, S
%A Gatto, L
%A Girke, T
%A Gottardo, R
%A Hahne, F
%A Hansen, K D
%A Irizarry, R A
%A Lawrence, M
%A Love, M I
%A MacDonald, J
%A Obenchain, V
%A Oleś, A K
%A Pagès, H
%A Reyes, A
%A Shannon, P
%A Smyth, G K
%A Tenenbaum, D
%A Waldron, L
%A Morgan, M
%D 2015
%J Nat Methods
%K SHOULDREAD bioconductor bioinformatics software
%N 2
%P 115-121
%R 10.1038/nmeth.3252
%T Orchestrating high-throughput genomic analysis with Bioconductor
%U https://www.ncbi.nlm.nih.gov/pubmed/25633503
%V 12
%X 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.
@article{Huber:2015:Nat-Methods:25633503,
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.},
added-at = {2017-06-09T08:54:51.000+0200},
author = {Huber, W and Carey, V J and Gentleman, R and Anders, S and Carlson, M and Carvalho, B S and Bravo, H C and Davis, S and Gatto, L and Girke, T and Gottardo, R and Hahne, F and Hansen, K D and Irizarry, R A and Lawrence, M and Love, M I and MacDonald, J and Obenchain, V and Oleś, A K and Pag{\`e}s, H and Reyes, A and Shannon, P and Smyth, G K and Tenenbaum, D and Waldron, L and Morgan, M},
biburl = {https://www.bibsonomy.org/bibtex/2533f1381b44aab6c4b9dc4f8bd50d6ea/marcsaric},
description = {Orchestrating high-throughput genomic analysis with Bioconductor. - PubMed - NCBI},
doi = {10.1038/nmeth.3252},
interhash = {8de67b09881ccf2a8e434c2d58b397b2},
intrahash = {533f1381b44aab6c4b9dc4f8bd50d6ea},
journal = {Nat Methods},
keywords = {SHOULDREAD bioconductor bioinformatics software},
month = feb,
number = 2,
pages = {115-121},
pmid = {25633503},
timestamp = {2017-06-09T08:54:51.000+0200},
title = {Orchestrating high-throughput genomic analysis with Bioconductor},
url = {https://www.ncbi.nlm.nih.gov/pubmed/25633503},
volume = 12,
year = 2015
}