Die chronologische Liste zeigt aktuelle Veröffentlichungen aus dem Forschungsbetrieb der Hochschule Weihenstephan-Triesdorf. Zuständig ist das Zentrum für Forschung und Wissenstransfer (ZFW).
Felipe Llinares-López,
Prof. Dr. Dominik Grimm,
Dean A Bodenham,
Udo Gieraths,
Mahito. Sugiyama,
Beth Rowan,
Karsten Borgwardt
Berechtigungen: Open Access
Berechtigungen: Peer Reviewed
Genome-wide detection of intervals of genetic heterogeneity associated with complex traits (2015) Bioinformatics 31 (12), S. i240-i249.
DOI: 10.1093/bioinformatics/btv263
Motivation: Genetic heterogeneity, the fact that several sequence variants give rise to the same phenotype, is a phenomenon that is of the utmost interest in the analysis of complex phenotypes. Current approaches for finding regions in the genome that exhibit genetic heterogeneity suffer from at least one of two shortcomings: (i) they require the definition of an exact interval in the genome that is to be tested for genetic heterogeneity, potentially missing intervals of high relevance, or (ii) they suffer from an enormous multiple hypothesis testing problem due to the large number of potential candidate intervals being tested, which results in either many false positives or a lack of power to detect true intervals.Results: Here, we present an approach that overcomes both problems: it allows one to automatically find all contiguous sequences of single nucleotide polymorphisms in the genome that are jointly associated with the phenotype. It also solves both the inherent computational efficiency problem and the statistical problem of multiple hypothesis testing, which are both caused by the huge number of candidate intervals. We demonstrate on Arabidopsis thalianagenome-wide association study data that our approach can discover regions that exhibit genetic heterogeneity and would be missed by single-locus mapping.Conclusions: Our novel approach can contribute to the genome-wide discovery of intervals that are involved in the genetic heterogeneity underlying complex phenotypes.Availability and implementation: The code can be obtained at: http://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/sis.html.
Prof. Dr. Dominik Grimm,
Chloé-Agathe Azencott,
Fabian Aicheler,
Udo Gieraths,
Daniel MacArthur,
Kaitlin Samocha,
David N Cooper,
Peter D Stenson,
Jordan W Smoller,
Laramie E Duncan,
Karsten Borgwardt
Berechtigungen: Open Access
Berechtigungen: Peer Reviewed
The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity (2015) Human Mutation 36 (5), S. 513-523.
DOI: 10.1002/humu.22768
Prioritizing missense variants for further experimental investigation is a key challenge in current sequencing studies for exploring complex and Mendelian diseases. A large number of in silico tools have been employed for the task of pathogenicity prediction, including PolyPhen‐2, SIFT, FatHMM, MutationTaster‐2, MutationAssessor, Combined Annotation Dependent Depletion, LRT, phyloP, and GERP++, as well as optimized methods of combining tool scores, such as Condel and Logit. Due to the wealth of these methods, an important practical question to answer is which of these tools generalize best, that is, correctly predict the pathogenic character of new variants. We here demonstrate in a study of 10 tools on five datasets that such a comparative evaluation of these tools is hindered by two types of circularity: they arise due to (1) the same variants or (2) different variants from the same protein occurring both in the datasets used for training and for evaluation of these tools, which may lead to overly optimistic results. We show that comparative evaluations of predictors that do not address these types of circularity may erroneously conclude that circularity confounded tools are most accurate among all tools, and may even outperform optimized combinations of tools.
Congmao Wang,
Chang Liu,
Damian Roqueiro,
Prof. Dr. Dominik Grimm,
Rebecca Schwab,
Claude Becker,
Christa Lanz,
Detlef Weigel
Berechtigungen: Open Access
Berechtigungen: Peer Reviewed
Genome-wide analysis of local chromatin packing in Arabidopsis thaliana (2015) Genome Research 25 , S. 246-256.
DOI: 10.1101/gr.170332.113
Mahito. Sugiyama,
Chloé-Agathe Azencott,
Prof. Dr. Dominik Grimm,
Yoshinobu Kawahara,
Karsten Borgwardt
Berechtigungen: Open Access
Berechtigungen: Peer Reviewed
Multi-Task Feature Selection on Multiple Networks via Maximum Flows (2014) Proceedings of the 2014 SIAM International Conference on Data Mining (SDM) 2014 , S. 199-207.
DOI: 10.1137/1.9781611973440.23
Chloé-Agathe Azencott,
Prof. Dr. Dominik Grimm,
Mahito. Sugiyama,
Yoshinobu Kawahara,
Karsten Borgwardt
Berechtigungen: Open Access
Berechtigungen: Peer Reviewed
Efficient network-guided multi-locus association mapping with graph cuts (2013) Bioinformatics 29 (13), S. i171-i179.
DOI: 10.1093/bioinformatics/btt238
Prof. Dr. Dominik Grimm,
Jörg Hagmann,
Daniel Koenig,
Detlef Weigel,
Karsten Borgwardt
Berechtigungen: Open Access
Berechtigungen: Peer Reviewed
Accurate indel prediction using paired-end short reads (2013) BMC Genomics 14 .
DOI: 10.1186/1471-2164-14-132
Aasa Feragen,
Jens Petersen,
Prof. Dr. Dominik Grimm,
Asger Dirksen,
Jesper Holst Pedersen,
Karsten Borgwardt,
Marleen de Bruijne
Berechtigungen: Peer Reviewed
Geometric tree kernels: Classification of COPD from airway tree geometry (2013) International Conference on Information Processing in Medical Imaging
IPMI 2013: Information Processing in Medical Imaging , S. 171-183.
DOI: 10.1007/978-3-642-38868-2_15
Guy Tsafnat,
Paul Setzermann,
Sally Partridge,
Prof. Dr. Dominik Grimm
Berechtigungen: Peer Reviewed
Computational inference of difficult word boundaries in DNA languages (2011) ISABEL '11: Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies 2011 .
DOI: 10.1145/2093698.2093709
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