Extending assembly of short DNA sequences to handle error

By William R. Jeck, Josephine A. Reinhardt, David A. Baltrus, M. Hickenbotham, Vincent J. Magrini, Elaine R. Mardis, Jeffery L. Dangl, Corbin D. Jones. Bioinform., 2007

295 citations recorded by the source corpus.

UNLABELLED Inexpensive de novo genome sequencing, particularly in organisms with small genomes, is now possible using several new sequencing technologies. Some of these technologies such as that from Illumina's Solexa Sequencing, produce high genomic coverage by generating a very large number of small reads ( approximately 30 bp). While prior work shows that partial assembly can be performed by k-mer extension in error-free reads, this algorithm is unsuccessful with the sequencing error rates found in practice. We present VCAKE (Verified Consensus Assembly by K-mer Extension), a modification of simple k-mer extension that overcomes error by using high depth coverage. Though it is a simple modification of a previous approach, we show significant improvements in assembly results on simulated and experimental datasets that include error. AVAILABILITY http://152.2.15.114/~labweb/VCAKE

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/78aeb46662833e9208a35fcdbbcb5badc45e3b62

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Citations in the corpus

Bioinformatics challenges of new sequencing technology. (2008, methodology): “SSAKE [22], VCAKE [ 23 ] and SHARCGS [24] all use a similar ‘greedy’ approach to genome assembly.”
Assembly Algorithms for Next-Generation Sequencing Data (2010, unknown): “VCAKE [34] is another iterative extension algorithm.”
Utilization of next-generation sequencing platforms in plant genomics and genetic variant discovery (2010, methodology): “A variety of tools that are beyond the scope of this paper have been developed for alignment and de novo assembly of short reads (for examples, see Warren et al. 2007; Dohm et al. 2007; Jeck et al. 2007; De Bona et al. 2008; Chaisson and Pevzner 2008; Li et al. 2008a; Smith et al. 2008; Zerbino and ”
NOVOPlasty: de novo assembly of organelle genomes from whole genome data (2016, methodology): “NOVOPlasty is a seed-extend based assembler similar to string overlap algorithms like SSAKE (14) and VCAKE (15).”
Stem cell transcriptome profiling via massive-scale mRNA sequencing (2008, methodology): “We clustered high-quality 35-mer tags that did not map to the genome or to the junction library using a modified version of the VCAK”
Genome assembly reborn: recent computational challenges (2009, background): “The reads are considered in decreasing order of their quality, as defined either by depth of coverage (number of reads confirming a section of a given read) [25] or by using a combination of coverage, quality values and the presence of at least one perfect overlap with”
ABySS: a parallel assembler for short read sequence data. (2009, unknown): “(Jeck et al. 2007).”
Ray: Simultaneous Assembly of Reads from a Mix of High-Throughput Sequencing Technologies (2010, background): “Over the course of this evolution, a number of algorithmic pathways were followed and quickly rendered obsolete by the sheer volume outputted by the new parallel sequencing technologies.”
De novo fragment assembly with short mate-paired reads: Does the read length matter? (2009, methodology): “VCAKE is an improvement of SSAKE and is able to assemble reads with higher error rate.”
ALLPATHS: de novo assembly of whole-genome shotgun microreads. (2008, background): “Several recent papers (Dohm et al. 2007; Jeck et al. 2007; Warren et al. 2007) have demonstrated assembly of unpaired microreads (for comparison, see Supplemental material Part j), but the quality of such assemblies is limited by the use of unpaired-read data.”
NOVOPlasty: de novo assembly of organelle genomes from whole genome data. (2016, methodology): “NOVOPlasty is a seed-extend based assembler similar to string overlap algorithms like SSAKE (14) and VCAKE (15).”