SpeedSeq: Ultra-fast personal genome analysis and interpretation
By Colby Chiang, Ryan M. Layer, Gregory G. Faust, Michael R. Lindberg, D. B. Rose, Erik P. Garrison, Gabor T. Marth, Aaron R. Quinlan, Ira M. Hall. Nature Methods, 2014
544 citations recorded by the source corpus.
SpeedSeq is an open-source genome analysis platform that accomplishes alignment, variant detection and functional annotation of a 50× human genome in 13 h on a low-cost server and alleviates a bioinformatics bottleneck that typically demands weeks of computation with extensive hands-on expert involvement. SpeedSeq offers performance competitive with or superior to current methods for detecting germline and somatic single-nucleotide variants, structural variants, insertions and deletions, and it includes novel functionality for streamlined interpretation.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/af9a140bcfea8f8461deb1dda885ba898e9b540a
Citations in the corpus
- High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios (2021, unknown): “The set of merged variants is then genotyped with svtyper (Chiang et al., 2015), followed by copy-number annotation with CNVnator (Abyzov et al.”
- Nanopore sequencing and assembly of a human genome with ultra-long reads (2017, unknown): “Using LUMPY 28 , we recalled SVs in the Platinum Genomes NA12878 Illumina data set (paired-end reads; European Nucleotide Archive, Run Accession ERR194147), intersected these calls with the aforementioned high confidence set, and genotyped the resulting calls using SVTyper 28 and the same Platinum a”
- Detection of mosaic and population-level structural variants with Sniffles2 (2024, unknown): “Here, we also detected somatic SVs but the presence/absence by means of the SUPP_VEC tag in the INFO field to extract cancer-specific SVs.”
- GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly (2017, unknown): “Both genotyping and incorporation of read depth is left to downstream programs such as SVTyper (Chiang et al. 2015) and CONSERTING (Chen et al. 2015).”