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Robert Vaser

Publications and source records attributed to Robert Vaser.

2 recordsLinked to original sources

Fast and accurate de novo genome assembly from long uncorrected reads

The assembly of long reads from Pacific Biosciences and Oxford Nanopore Technologies typically requires resource intensive error correction and consensus generation steps to obtain high quality assemblies. We show that the error correction step can be omitted and high quality consensus sequences can be generated efficiently with a SIMD accelerated, partial order alignment based stand-alone consensus module called Racon. Based on tests with PacBio and Oxford Nanopore datasets we show that Racon coupled with Miniasm enables consensus genomes with similar or better quality than state-of-the-art methods while being an order of magnitude faster.\n\nRacon is available open source under the MIT license at https://github.com/isovic/racon.git.

Bioinformatics

SWORD - a highly efficient protein database search

MotivationProtein database search is one of the fundamental problems in bioinformatics. For decades, it has been explored and solved using different exact and heuristic approaches. However, exponential growth of data in size in recent years has brought significant challenges in improving already existing algorithms. BLASTP has been the most successful tool for protein database search, but is also becoming a bottleneck in many applications. Due to that, many different approaches have been developed to comple-ment or replace BLASTP. In this paper, we present SWORD, an efficient protein database search implementation that runs 3-4 faster than BLASTP in the sensitive mode and up to 18 faster in the fast and less accurate mode and also provides guaranteed optimal alignments for candidate sequences. SWORD is designed to be used in nearly all database search environments, but is especially suitable for large databases. Its sensitivity exceeds that of BLASTP for majority of input datasets.\n\nAvailabilitySword is freely available for download from https://github.com/rvaser/sword\n\nContactrobert.vaser@fer.hr, mile.sikic@fer.hr

Bioinformatics