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Konrad Scheffler

Researcher at Illumina

Publications -  55
Citations -  6860

Konrad Scheffler is an academic researcher from Illumina. The author has contributed to research in topics: Selection (genetic algorithm) & Phylogenetic tree. The author has an hindex of 27, co-authored 53 publications receiving 5192 citations. Previous affiliations of Konrad Scheffler include University of Cape Town & University of California, San Diego.

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Journal ArticleDOI

Detecting individual sites subject to episodic diversifying selection.

TL;DR: It is found that episodic selection is widespread and it is concluded that the number of sites experiencing positive selection may have been vastly underestimated.
Journal ArticleDOI

FUBAR : A Fast, Unconstrained Bayesian AppRoximation for inferring selection

TL;DR: This work presents an approximate hierarchical Bayesian method using a Markov chain Monte Carlo (MCMC) routine that ensures robustness against model misspecification by averaging over a large number of predefined site classes, and leaves the distribution of selection parameters essentially unconstrained.
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Strelka2: fast and accurate calling of germline and somatic variants.

TL;DR: Strelka2 introduces a novel mixture-model-based estimation of insertion/deletion error parameters from each sample, an efficient tiered haplotype-modeling strategy, and a normal sample contamination model to improve liquid tumor analysis.
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Less is More: an Adaptive Branch-Site Random Effects Model for Efficient Detection of Episodic Diversifying Selection

TL;DR: Adaptive branch-site random effects likelihood (aBSREL), whose key innovation is variable parametric complexity chosen with an information theoretic criterion, delivers statistical performance matching or exceeding best-in-class existing approaches, while running an order of magnitude faster.
Journal ArticleDOI

RELAX: Detecting Relaxed Selection in a Phylogenetic Framework

TL;DR: This work presents a general hypothesis testing framework (RELAX) for detecting relaxed selection in a codon-based phylogenetic framework and demonstrates the power of RELAX in a variety of biological scenarios where relaxation of selection has been hypothesized or demonstrated previously.