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ralphi: a deep reinforcement learning framework for haplotype assembly
Abstract Haplotype assembly is the problem of reconstructing the combination of alleles on the maternally and paternally inherited chromosome copies. Individual haplotypes are essential to our understanding of how combinations of different variants impact phenotype. In this work, we focus on read-based haplotype assembly of individual diploid genomes, which reconstructs the two haplotypes directly from read alignments at variant loci.
Designing efficient randstrobes for sequence similarity analyses
Abstract Substrings of length k, commonly referred to as k-mers, play a vital role in sequence analysis, reducing the search space by providing anchors between queries and references. However, k-mers are limited to exact matches between sequences. This has led to alternative constructs, such as spaced k-mers, that can match across substitutions. We recently introduced a class of new constructs, strobemers, that can match across substitutions and smaller insertions and deletions.
Efficient minimizer orders for large values of k using minimum decycling sets
David Pellow1, Lianrong Pu1, Bariş Ekim2, Lior Kotlar3, Bonnie Berger2,4, Ron Shamir1 and Yaron Orenstein5,6 1Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv 6997801, Israel; 2Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; 3Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel; 4Department of Mathematics, Massachusetts Institute of Technology,...
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