Biology subjects

Yeo, S.

Publications and source records attributed to Yeo, S..

3 recordsLinked to original sources

bioRxiv2018

Improving on hash-based probabilistic sequence classification using multiple spaced seeds and multi-index Bloom filters

Alignment-free classification of sequences against collections of sequences has enabled high-throughput processing of sequencing data in many bioinformatics analysis pipelines. Originally hash-table based, much work has been done to improve and reduce the memory requirement of indexing of k-mer sequences with probabilistic indexing strategies. These efforts have led to lower memory highly efficient indexes, but often lack sensitivity in the face of sequencing errors or polymorphism because they are k-mer based. To address this, we designed a new memory efficient data structure that can tolerate mismatches using multiple spaced seeds, called a multi-index Bloom Filter. Implemented as part of BioBloom Tools, we demonstrate our algorithm in two applications, read binning for targeted assembly and taxonomic read assignment. Our tool shows a higher sensitivity and specificity for read-binning than BWA MEM at an order of magnitude less time. For taxonomic classification, we show higher sensitivity than CLARK-S at an order of magnitude less time while using half the memory.

bioinformatics↗

bioRxiv2018

Tigmint: Correcting Assembly Errors Using Linked Reads From Large Molecules

Genome sequencing yields the sequence of many short snippets of DNA (reads) from a genome. Genome assembly attempts to reconstruct the original genome from which these reads were derived. This task is difficult due to gaps and errors in the sequencing data, repetitive sequence in the underlying genome, and heterozygosity, and assembly errors are common. These misassemblies may be identified by comparing the sequencing data to the assembly, and by looking for discrepancies between the two. Once identified, these misassemblies may be corrected, improving the quality of the assembly. Although tools exist to identify and correct misassemblies using Illumina pair-end and mate-pair sequencing, no such tool yet exists that makes use of the long distance information of the large molecules provided by linked reads, such as those offered by the 10x Genomics Chromium platform. We have developed the tool Tigmint for this purpose. To demonstrate the effectiveness of Tigmint, we corrected assemblies of a human genome using short reads assembled with ABySS 2.0 and other assemblers. Tigmint reduced the number of misassemblies identified by QUAST in the ABySS assembly by 216 (27%). While scaffolding with ARCS alone more than doubled the scaffold NGA50 of the assembly from 3 to 8 Mbp, the combination of Tigmint and ARCS improved the scaffold NGA50 of the assembly over five-fold to 16.4 Mbp. This notable improvement in contiguity highlights the utility of assembly correction in refining assemblies. We demonstrate its usefulness in correcting the assemblies of multiple tools, as well as in using Chromium reads to correct and scaffold assemblies of long single-molecule sequencing. The source code of Tigmint is available for download from https://github.com/bcgsc/tigmint, and is distributed under the GNU GPL v3.0 license.

genomics↗

bioRxiv2017

ARCS: Assembly Roundup by Chromium Scaffolding

Sequencing of human genomes is now routine, and assembly of shotgun reads is increasingly feasible. However, assemblies often fail to inform about chromosome-scale structure due to lack of linkage information over long stretches of DNA - a shortcoming that is being addressed by new sequencing protocols, such as linked reads from 10X Genomics. Here we present ARCS, an application that utilizes the barcoding information contained in linked reads to further organize draft genomes into highly contiguous assemblies. We show how the contiguity of an ABySS H. sapiens genome assembly can be increased over six-fold using moderate coverage (25-fold) Chromium data. We expect ARCS to have broad utility in harnessing the barcoding information contained in Chromium data for connecting high-quality sequences in genome assembly drafts. Availability: http://www.bcgsc.ca/platform/bioinfo/software/arcs\n\nSupplementary information available online.

genomics↗