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  • 2010-2014  (2)
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  • 1
    Publikationsdatum: 2013-01-19
    Beschreibung: A variety of genome-wide profiling techniques are available to investigate complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we highlight common approaches to genomic data integration and provide a transparent benchmarking procedure to quantitatively compare method performances in cancer gene prioritization. Algorithms, data sets and benchmarking results are available at http://intcomp.r-forge.r-project.org .
    Print ISSN: 1467-5463
    Digitale ISSN: 1477-4054
    Thema: Biologie , Informatik
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 2013-06-24
    Beschreibung: Motivation: Bisulfite sequencing is currently the gold standard to obtain genome-wide DNA methylation profiles in eukaryotes. In contrast to the rapid development of appropriate pre-processing and alignment software, methods for analyzing the resulting methylation profiles are relatively limited so far. For instance, an appropriate pipeline to detect DNA methylation differences between cancer and control samples is still required. Results: We propose an algorithm that detects significantly differentially methylated regions in data obtained by targeted bisulfite sequencing approaches, such as reduced representation bisulfite sequencing. In a first step, this approach tests all target regions for methylation differences by taking spatial dependence into account. A false discovery rate procedure controls the expected proportion of incorrectly rejected regions. In a second step, the significant target regions are trimmed to the actually differentially methylated regions. This hierarchical procedure detects differentially methylated regions with increased power compared with existing methods. Availability: R/Bioconductor package BiSeq. Contact: katja.hebestreit@uni-muenster.de Supplementary information: Supplementary Data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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