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    Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation (2012)
    Oxford University Press
    Details
    Publikationsdatum: 2012-05-23
    Beschreibung: A flexible statistical framework is developed for the analysis of read counts from RNA-Seq gene expression studies. It provides the ability to analyse complex experiments involving multiple treatment conditions and blocking variables while still taking full account of biological variation. Biological variation between RNA samples is estimated separately from the technical variation associated with sequencing technologies. Novel empirical Bayes methods allow each gene to have its own specific variability, even when there are relatively few biological replicates from which to estimate such variability. The pipeline is implemented in the edgeR package of the Bioconductor project. A case study analysis of carcinoma data demonstrates the ability of generalized linear model methods (GLMs) to detect differential expression in a paired design, and even to detect tumour-specific expression changes. The case study demonstrates the need to allow for gene-specific variability, rather than assuming a common dispersion across genes or a fixed relationship between abundance and variability. Genewise dispersions de-prioritize genes with inconsistent results and allow the main analysis to focus on changes that are consistent between biological replicates. Parallel computational approaches are developed to make non-linear model fitting faster and more reliable, making the application of GLMs to genomic data more convenient and practical. Simulations demonstrate the ability of adjusted profile likelihood estimators to return accurate estimators of biological variability in complex situations. When variation is gene-specific, empirical Bayes estimators provide an advantageous compromise between the extremes of assuming common dispersion or separate genewise dispersion. The methods developed here can also be applied to count data arising from DNA-Seq applications, including ChIP-Seq for epigenetic marks and DNA methylation analyses.
    Schlagwort(e): Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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    The landscape of somatic copy-number alteration across human cancers (2010)
    Nature Publishing Group (NPG)
    Details
    Publikationsdatum: 2010-02-19
    Beschreibung: A powerful way to discover key genes with causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Here we present high-resolution analyses of somatic copy-number alterations (SCNAs) from 3,131 cancer specimens, belonging largely to 26 histological types. We identify 158 regions of focal SCNA that are altered at significant frequency across several cancer types, of which 122 cannot be explained by the presence of a known cancer target gene located within these regions. Several gene families are enriched among these regions of focal SCNA, including the BCL2 family of apoptosis regulators and the NF-kappaBeta pathway. We show that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival. Finally, we demonstrate that a large majority of SCNAs identified in individual cancer types are present in several cancer types.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2826709/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2826709/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Beroukhim, Rameen -- Mermel, Craig H -- Porter, Dale -- Wei, Guo -- Raychaudhuri, Soumya -- Donovan, Jerry -- Barretina, Jordi -- Boehm, Jesse S -- Dobson, Jennifer -- Urashima, Mitsuyoshi -- Mc Henry, Kevin T -- Pinchback, Reid M -- Ligon, Azra H -- Cho, Yoon-Jae -- Haery, Leila -- Greulich, Heidi -- Reich, Michael -- Winckler, Wendy -- Lawrence, Michael S -- Weir, Barbara A -- Tanaka, Kumiko E -- Chiang, Derek Y -- Bass, Adam J -- Loo, Alice -- Hoffman, Carter -- Prensner, John -- Liefeld, Ted -- Gao, Qing -- Yecies, Derek -- Signoretti, Sabina -- Maher, Elizabeth -- Kaye, Frederic J -- Sasaki, Hidefumi -- Tepper, Joel E -- Fletcher, Jonathan A -- Tabernero, Josep -- Baselga, Jose -- Tsao, Ming-Sound -- Demichelis, Francesca -- Rubin, Mark A -- Janne, Pasi A -- Daly, Mark J -- Nucera, Carmelo -- Levine, Ross L -- Ebert, Benjamin L -- Gabriel, Stacey -- Rustgi, Anil K -- Antonescu, Cristina R -- Ladanyi, Marc -- Letai, Anthony -- Garraway, Levi A -- Loda, Massimo -- Beer, David G -- True, Lawrence D -- Okamoto, Aikou -- Pomeroy, Scott L -- Singer, Samuel -- Golub, Todd R -- Lander, Eric S -- Getz, Gad -- Sellers, William R -- Meyerson, Matthew -- K08 AR055688/AR/NIAMS NIH HHS/ -- K08 AR055688-03/AR/NIAMS NIH HHS/ -- K08 AR055688-04/AR/NIAMS NIH HHS/ -- K08 CA122833/CA/NCI NIH HHS/ -- K08 CA122833-01A1/CA/NCI NIH HHS/ -- K08 CA122833-02/CA/NCI NIH HHS/ -- K08 CA122833-03/CA/NCI NIH HHS/ -- K08 CA134931/CA/NCI NIH HHS/ -- K08CA122833/CA/NCI NIH HHS/ -- P01CA 098101/CA/NCI NIH HHS/ -- P01CA085859/CA/NCI NIH HHS/ -- P50CA90578/CA/NCI NIH HHS/ -- R01 CA109038/CA/NCI NIH HHS/ -- R01 GM074024/GM/NIGMS NIH HHS/ -- R01CA109038/CA/NCI NIH HHS/ -- R01CA109467/CA/NCI NIH HHS/ -- T32 GM007753/GM/NIGMS NIH HHS/ -- U24 CA126546/CA/NCI NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2010 Feb 18;463(7283):899-905. doi: 10.1038/nature08822.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Cancer Program and Medical and Population Genetics Group, The Broad Institute of M.I.T. and Harvard, 7 Cambridge Center.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20164920" target="_blank"〉PubMed〈/a〉
    Schlagwort(e): Apoptosis/genetics ; Cell Line, Tumor ; Cell Survival/genetics ; DNA Copy Number Variations/*genetics ; Gene Amplification/genetics ; Gene Dosage/*genetics ; Genomics ; Humans ; Multigene Family/genetics ; Myeloid Cell Leukemia Sequence 1 Protein ; Neoplasms/classification/*genetics/pathology ; Proto-Oncogene Proteins c-bcl-2/genetics ; Signal Transduction ; bcl-X Protein/genetics
    Print ISSN: 0028-0836
    Digitale ISSN: 1476-4687
    Thema: Biologie , Chemie und Pharmazie , Medizin , Allgemeine Naturwissenschaft , Physik
    Publiziert von Nature Publishing Group (NPG)
    Standort Signatur Erwartet Verfügbarkeit
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