SKESA: strategic k-mer extension for scrupulous assemblies
By Alexandre Souvorov, Richa Agarwala, David J. Lipman. Genome Biology, 2018
583 citations recorded by the source corpus.
SKESA is a DeBruijn graph-based de-novo assembler designed for assembling reads of microbial genomes sequenced using Illumina. Comparison with SPAdes and MegaHit shows that SKESA produces assemblies that have high sequence quality and contiguity, handles low-level contamination in reads, is fast, and produces an identical assembly for the same input when assembled multiple times with the same or different compute resources. SKESA has been used for assembling over 272,000 read sets in the Sequence Read Archive at NCBI and for real-time pathogen detection. Source code for SKESA is freely available at https://github.com/ncbi/SKESA/releases.
Subfields: Ecology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/119ee940a06d78dce2b9ba21fe31835abe0e4936
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Citations in the corpus
- Validating the AMRFinder Tool and Resistance Gene Database by Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of Isolates (2019, unknown): “AMR gene identification, NCBI has developed an assembler that emphasizes base accuracy, increasing the reliability of allele identification (38).”
- Performance of neural network basecalling tools for Oxford Nanopore sequencing (2019, methodology): “Illumina reads were also available for all genomes, and we used SKESA6 (v2.”