File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Glbase: A framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data

TitleGlbase: A framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data
Authors
KeywordsGenomics
ChIP-seq
Microarray
Motifs
RNA-seq
Transcription factor
Bioinformatics
Issue Date2014
Citation
Cell Regeneration, 2014, v. 3, n. 1 How to Cite?
Abstract© 2014 Hutchins et al.; licensee BioMed Central Ltd. Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data), and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.
Persistent Identifierhttp://hdl.handle.net/10722/253119

 

DC FieldValueLanguage
dc.contributor.authorHutchins, Andrew P.-
dc.contributor.authorJauch, Ralf-
dc.contributor.authorDyla, Mateusz-
dc.contributor.authorMiranda-Saavedra, Diego-
dc.date.accessioned2018-05-11T05:38:39Z-
dc.date.available2018-05-11T05:38:39Z-
dc.date.issued2014-
dc.identifier.citationCell Regeneration, 2014, v. 3, n. 1-
dc.identifier.urihttp://hdl.handle.net/10722/253119-
dc.description.abstract© 2014 Hutchins et al.; licensee BioMed Central Ltd. Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data), and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.-
dc.languageeng-
dc.relation.ispartofCell Regeneration-
dc.subjectGenomics-
dc.subjectChIP-seq-
dc.subjectMicroarray-
dc.subjectMotifs-
dc.subjectRNA-seq-
dc.subjectTranscription factor-
dc.subjectBioinformatics-
dc.titleGlbase: A framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-84988231210-
dc.identifier.volume3-
dc.identifier.issue1-
dc.identifier.spagenull-
dc.identifier.epagenull-
dc.identifier.eissn2045-9769-
dc.identifier.issnl2045-9769-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats