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334:"s that are designed to demonstrate how a particular task can be accomplished with that package's software. Others provide a more thorough overview of the package or might even discuss general issues related to the package. In the future, the Bioconductor project is looking towards providing vignettes that are not specifically tied to a package, but rather are demonstrating more complex concepts. As with all aspects of the Bioconductor project, users are encouraged to participate in this effort.
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many
Bioconductor packages have been developed to meet various data analysis needs. The use of these packages provides a basic understanding of the R programming / command language. As a result, R and Bioconductor packages, which have a strong computing background, are used by most biologists who will benefit significantly from their ability to analyze datasets. All these results provide biologists with easy access to the analysis of genomic data without requiring programming
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While computational methods continue to be developed to interpret biological data, the
Bioconductor project is an open source software repository that hosts a wide range of statistical tools developed in the R programming environment. Utilizing a rich array of statistical and graphical features in R,
560:
Each release of
Bioconductor is developed to work best with a chosen version of R. In addition to bugfixes and updates, a new release typically adds packages. The table below maps a Bioconductor release to a R version and shows the number of available Bioconductor software packages for that release.
412:(annotate package). Functions are also provided for incorporating the results of statistical analysis in HTML reports with links to annotation WWW resources. Software tools are available for assembling and processing genomic annotation data, from databases such as
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Each
Bioconductor package contains at least one vignette, which is a document that provides a textual, task-oriented description of the package's functionality. These vignettes come in several forms. Many are simple
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The
Bioconductor project aims to provide access to a wide range of powerful statistical and graphical methods for the analysis of genomic data. Analysis packages are available for: pre-processing
543:, either by contributing Bioconductor compliant packages or documentation. Additionally Bioconductor provides a mechanism for linking together different groups with
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microarrays. As the project has matured, the functional scope of the software packages broadened to include the analysis of all types of genomic data, such as SAGE,
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AnnotationDbi package. Data packages are distributed to provide mappings between different probe identifiers (e.g. Affy IDs, LocusLink,
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The
Bioconductor project provides software for associating microarray and other genomic data in real time to biological metadata from web databases such as
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Computational Biology Solutions Using R and Bioconductor
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Further scientific understanding by producing high-quality
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in the analysis of genomic data, e.g. literature data from
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on software, possibly at the level of shared development.
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Provide widespread access to a broad range of powerful
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software project for the analysis and comprehension of
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R is a programming language for statistical computing.
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16:Software project for the analysis of genomic data
217:Most Bioconductor components are distributed as
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495:scientific computing and statistical practice
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483:To facilitate software improvements through
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1391:List of open source bioinformatics software
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1514:CDs providing BioConductor installations.
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261:methods for the analysis of genomic data.
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249:The broad goals of the projects are to:
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325:Documentation and reproducible research
308:documentation and reproducible research
167:Bioconductor is based primarily on the
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1432:"Bioconductor – Release Announcements"
207:Fred Hutchinson Cancer Research Center
7:
1359:Free and open-source software portal
1396:List of sequence alignment software
1413:, a microarray technology platform
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473:in general. The reasons include:
339:Statistical and graphical methods
272:, annotation data from LocusLink/
1487:distribution strives towards an
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539:are encouraged to become
426:UCSC Human Genome Project
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1401:R (programming language)
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480:and their implementation
418:Gene Ontology Consortium
355:array data; identifying
225:and two or more channel
1506:are projects extending
283:that enables the rapid
367:techniques, including
172:R programming language
90:R programming language
46:; 4 months ago
1483:The community of the
1479:Bioconductor Releases
1381:Computational biology
1249:; Falcon, S. (2008).
523:reproducible research
471:computational biology
1271:Gentleman, Robert C.
511:is the owner of the
509:scientific community
114:Artistic License 2.0
455:open source license
266:biological metadata
184:development version
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1494:2007-08-11 at the
1285:; Iacus, Stefano;
502:workbench of tools
493:To encourage good
156:data generated by
1262:978-0-387-77239-4
1233:978-1-4200-6367-7
1209:978-0-387-25146-2
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400:Genome annotation
389:survival analysis
281:software platform
279:Provide a common
188:genome annotation
162:molecular biology
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1512:Debian GNU/Linux
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20:Bioconductor
1311:(10): R80.
1241:Hahne, F.;
1143:19 Oct 2002
1125:29 May 2003
1107:30 Oct 2003
1089:17 May 2004
1071:25 Oct 2004
1053:18 May 2005
1035:14 Oct 2005
1017:27 Apr 2006
981:26 Apr 2007
927:22 Oct 2008
909:21 Apr 2009
891:28 Oct 2009
873:23 Apr 2010
855:18 Nov 2010
837:14 Apr 2011
783:15 Oct 2013
765:14 Oct 2014
747:14 Oct 2015
729:18 Oct 2016
711:31 Oct 2017
693:31 Oct 2018
675:30 Oct 2019
657:28 Apr 2020
639:27 Oct 2021
603:25 Oct 2023
521:To promote
445:Open source
393:time series
361:statistical
285:development
255:statistical
192:microarrays
169:statistical
146:open source
1522:Categories
1500:BioKnoppix
1418:References
1411:Affymetrix
1196:Dudoit, S.
1161:1 May 2002
999:4 Oct 2006
963:8 Oct 2007
945:1 May 2008
819:1 Nov 2011
801:3 Oct 2012
621:2 Nov 2022
585:1 May 2024
556:Milestones
547:to foster
541:developers
485:bug fixing
478:algorithms
385:resampling
381:prediction
375:modeling,
373:non-linear
345:Affymetrix
289:deployment
223:Affymetrix
219:R packages
51:2024-05-01
1243:Huber, W.
1188:Huber, W.
1177:Resources
395:analysis.
365:graphical
303:software.
293:plug-able
259:graphical
200:expertise
1504:Quantian
1492:Archived
1345:See also
1337:15461798
1220:(2008).
1198:(2005).
567:Version
489:plug-ins
457:such as
438:phytools
349:Illumina
297:scalable
235:sequence
213:Packages
176:releases
85:Platform
1508:Knoppix
422:UniGene
414:GenBank
406:GenBank
158:wet lab
154:genomic
120:Website
109:License
78:Windows
49: (
1442:28 May
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899:R 2.10
881:R 2.11
863:R 2.12
845:R 2.13
827:R 2.14
809:R 2.15
434:ggtree
430:PubMed
424:, the
416:, the
410:PubMed
391:, and
369:linear
332:How-to
299:, and
274:Entrez
270:PubMed
241:data.
1169:R 1.5
1151:R 1.6
1133:R 1.7
1115:R 1.8
1097:R 1.9
1079:R 2.0
1061:R 2.1
1043:R 2.2
1025:R 2.3
1007:R 2.4
989:R 2.5
971:R 2.6
953:R 2.7
935:R 2.8
917:R 2.9
797:2.11
791:R 3.0
779:2.13
773:R 3.1
755:R 3.2
751:1104
737:R 3.3
733:1296
719:R 3.4
715:1473
701:R 3.5
697:1649
683:R 3.6
679:1823
671:3.10
665:R 4.0
661:1903
653:3.11
647:R 4.1
643:2083
635:3.14
629:R 4.2
625:2183
617:3.16
611:R 4.3
607:2266
599:3.18
593:R 4.4
589:2300
581:3.19
537:Users
465:, or
245:Goals
237:, or
231:Oligo
140:is a
74:macOS
70:Linux
1502:and
1444:2019
1333:PMID
1257:ISBN
1228:ISBN
1204:ISBN
1157:1.0
1139:1.1
1121:1.2
1103:1.3
1085:1.4
1075:100
1067:1.5
1057:123
1049:1.6
1039:141
1031:1.7
1021:172
1013:1.8
1003:188
995:1.9
985:214
977:2.0
967:233
959:2.1
949:260
941:2.2
931:294
923:2.3
913:320
905:2.4
895:352
887:2.5
877:389
869:2.6
859:418
851:2.7
841:466
833:2.8
823:517
815:2.9
805:610
787:749
769:934
761:3.0
743:3.2
725:3.4
707:3.6
689:3.8
487:and
463:GPL2
371:and
363:and
353:cDNA
347:and
287:and
257:and
227:cDNA
148:and
142:free
129:.org
97:Type
1473:GNU
1323:PMC
1313:doi
1165:15
1147:20
1129:30
1111:49
1093:81
467:BSD
291:of
239:SNP
125:www
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1245:;
1194:;
1190:;
461:,
436:,
387:,
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