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We present a new clustering algorithm by proposing a convex relaxation of hierarchical clustering, which results in a family of objective functions with a natural geometric interpretation. We give efficient algorithms for calculating the continuous regularization path of solutions, and discuss relative advantages of the parameters. Our method experimentally(More)
We describe the use of zinc-finger nucleases (ZFNs) for somatic and germline disruption of genes in zebrafish (Danio rerio), in which targeted mutagenesis was previously intractable. ZFNs induce a targeted double-strand break in the genome that is repaired to generate small insertions and deletions. We designed ZFNs targeting the zebrafish golden and no(More)
BACKGROUND The recent advent of high-throughput SNP genotyping technologies has opened new avenues of research for population genetics. In particular, a growing interest in the identification of footprints of selection, based on genome scans for adaptive differentiation, has emerged. METHODOLOGY/PRINCIPAL FINDINGS The purpose of this study is to develop(More)
Many models have been proposed to detect copy number alterations in chromosomal copy number profiles, but it is usually not obvious to decide which is most effective for a given data set. Furthermore, most methods have a smoothing parameter that determines the number of breakpoints and must be chosen using various heuristics. We present three contributions(More)
In segmentation models, the number of change-points is typically chosen using a penalized cost function. In this work, we propose to learn the penalty and its constants in databases of signals with weak change-point annotations. We propose a convex relaxation for the resulting interval regression problem, and solve it using accelerated proximal gradient(More)
MOTIVATION DNA copy number profiles characterize regions of chromosome gains, losses and breakpoints in tumor genomes. Although many models have been proposed to detect these alterations, it is not clear which model is appropriate before visual inspection the signal, noise and models for a particular profile. RESULTS We propose SegAnnDB, a Web-based(More)
The R package quadprog provides the function solve.QP(D, d, A, b 0), which solves the following optimization problem: min b∈R v 1 2 b Db − d b subject to A b b 0 (1) where D ∈ R v×v , d ∈ R v , A ∈ R v×k , b 0 ∈ R k , v is the number of optimization variables, k is the number of inequality constraints, and x y is componentwise inequality, which implies x i(More)