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	Provedor de dados Nature Precedings (2) Autor Oliver Stegle (2) Gunnar Rätsch (1) Karsten Borgwardt (1) Neil Lawrence (1) Nicolo Fusi (1) Philipp Drewe (1) Regina Bohnert (1) Mais... Palavra-chave Bioinformatics (2) Genetics & Genomics (2) Biotechnology (1) Molecular Cell Biology (1) Tipo do documento Manuscript (2) Ano 2011 (1) 2010 (1) País United Kingdom (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Statistical Tests for Detecting Differential RNA-Transcript Expression from Read Counts Nature Precedings Oliver Stegle; Philipp Drewe; Regina Bohnert; Karsten Borgwardt; Gunnar Rätsch. As a fruit of the current revolution in sequencing technology, transcriptomes can now be analyzed at an unprecedented level of detail. These advances have been exploited for detecting differential expressed genes across biological samples and for quantifying the abundances of various RNA transcripts within one gene. However, explicit strategies for detecting the hidden differential abundances of RNA transcripts in biological samples have not been defined. In this work, we present two novel statistical tests to address this issue: a 'gene structure sensitive' Poisson test for detecting differential expression when the transcript structure of the gene is known, and a kernel-based test called Maximum Mean Discrepancy when it is unknown. We... Tipo: Manuscript Palavras-chave: Biotechnology; Genetics & Genomics; Molecular Cell Biology; Bioinformatics. Ano: 2010 URL: http://precedings.nature.com/documents/4437/version/1 Accurate modeling of confounding variation in eQTL studies leads to a great increase in power to detect trans-regulatory effects Nature Precedings Nicolo Fusi; Oliver Stegle; Neil Lawrence. Expression quantitative trait loci (eQTL) studies are an integral tool to investigate the genetic component of gene expression variation. A major challenge in the analysis of such studies are hidden confounding factors, such as unobserved covariates or unknown environmental influences. These factors can induce a pronounced artifactual correlation structure in the expression profiles, which may create spurious false associations or mask real genetic association signals. 

Here, we report PANAMA (Probabilistic ANAlysis of genoMic dAta), a novel probabilistic model to account for confounding factors within an
eQTL analysis. In contrast to previous methods, PANAMA learns hidden factors jointly with the... Tipo: Manuscript Palavras-chave: Genetics & Genomics; Bioinformatics. Ano: 2011 URL: http://precedings.nature.com/documents/5995/version/1 Registros recuperados: 2 Primeira ... 1 ... Última

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