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glbase:a framework for combining,analyzing and displaying heterogeneous genomic and high-throughput sequencing data

Cell Regeneration 2014年第1期3卷 1-20页

作者： Andrew Paul Hutchins Ralf Jauch mateusz dyla.diego miranda-saavedra Key Laboratory of Regenerative Biology South China Institute for Stem Cell Biology and Regenerative MedicineGuangzhou Institutes of Biomedicine and HealthChinese Academy of SciencesGuangzhou 510530China Genome Regulation Laboratory South China Institute for Stem Cell Biology and Regenerative MedicineGuangzhou Institutes of Biomedicine and HealthChinese Academy of SciencesGuangzhou 510530China Laboratory for Structural Biochemistry Genome Institute of Singapore60 Biopolis StreetSingapore 138672Singapore Department of Molecular Biology and Genetics Aarhus UniversityAarhusDenmark Fibrosis Laboratories Institute of Cellular MedicineNewcastle University Medical SchoolFramlington PlaceNewcastle upon Tyne NE24HHUK

Genomic datasets and the tools to analyze them have proliferated at an astonishing ***,such tools are often poorly integrated with each other:each program typically produces its own custom output in a variety of non-standard file *** we present glbase,a framework that uses a flexible set of descriptors that can quickly parse non-binary data *** 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 *** 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 *** is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data *** 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 *** is freely available at http://***/oaxiom/glbase/.

关键词： ChIP-seq RNA-seq Genomics Microarray Motifs Transcription factor Bioinformatics

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