Dally, W. J. | bioRxiv Science

bioRxiv2019

Champagne: Whole-genome phylogenomic character matrix method places Myomorpha basal in Rodentia

We present Champagne, a whole-genome method for generating character matrices for phylogenomic analysis using large genomic events that, by rigorously picking orthologous genes and locating large, virtually homoplasy-free insertion and deletion events, delivers a character matrix that outperforms existing morphological and nucleotide-based matrices on both established phylogenies, and difficult-to-resolve nodes in the mammalian tree. Champagne harbors distinct theoretical advantages, and can easily be run on any clade of related species, of the many currently being sequenced. Champagne considerably improves the retention index in the parsimony analysis of a number of widely established topologies, observes incomplete lineage sorting (ILS) at the root of Paenungulata, finds little evidence for human-chimp-gorilla ILS, and most surprisingly, offers convincing evidence for a reconsideration of squirrels position in the rodent tree.

evolutionary biology↗

bioRxiv2017

Darwin: A Hardware-acceleration Framework for Genomic Sequence Alignment

Genomics is set to transform medicine and our understanding of life in fundamental ways. But the growth in genomics data has been overwhelming - far outpacing Moores Law. The advent of third generation sequencing technologies is providing new insights into genomic contribution to diseases with complex mutation events, but have prohibitively high computational costs. Over 1,300 CPU hours are required to align reads from a 54x coverage of the human genome to a reference (estimated using [1]), and over 15,600 CPU hours to assemble the reads de novo [2]. This paper proposes \"Darwin\" - a hardware-accelerated framework for genomic sequence alignment that, without sacrificing sensitivity, provides 125x and 15.6x speedup over the state-of-the-art software counterparts for reference-guided and de novo assembly of third generation sequencing reads, respectively. For pairwise alignment of sequences, Darwin is over 39,000x more energy-efficient than software. Darwin uses (i) a novel filtration strategy, called D-SOFT, to reduce the search space for sequence alignment at high speed, and (ii) a hardware-accelerated version of GACT, a novel algorithm to generate near-optimal alignments of arbitrarily long genomic sequences using constant memory for trace-back. Darwin is adaptable, with tunable speed and sensitivity to match emerging sequencing technologies and to meet the requirements of genomic applications beyond read assembly.

genomics↗