Accurate detection of complex structural variations using single molecule sequencing

By Fritz J. Sedlazeck, Philipp Rescheneder, Moritz Smolka, Han Fang, Maria Nattestad, A. von Haeseler, Michael C. Schatz. Nature Methods, 2017

1,457 citations recorded by the source corpus.

Structural variations are the greatest source of genetic variation, but they remain poorly understood because of technological limitations. Single-molecule long-read sequencing has the potential to dramatically advance the field, although high error rates are a challenge with existing methods. Addressing this need, we introduce open-source methods for long-read alignment (NGMLR; https://github.com/philres/ngmlr) and structural variant identification (Sniffles; https://github.com/fritzsedlazeck/Sniffles) that provide unprecedented sensitivity and precision for variant detection, even in repeat-rich regions and for complex nested events that can have substantial effects on human health. In several long-read datasets, including healthy and cancerous human genomes, we discovered thousands of novel variants and categorized systematic errors in short-read approaches. NGMLR and Sniffles can automatically filter false events and operate on low-coverage data, thereby reducing the high costs that have hindered the application of long reads in clinical and research settings. NGMLR and Sniffles perform highly accurate alignment and structural variation detection from long-read sequencing data.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/28f1d3efbbac94fecdafda8341491670ec535ac3

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Citations in the corpus

JBrowse 2: a modular genome browser with views of synteny and structural variation (2022, methodology): “G The SV Inspector allows inspection of structural variants by combining a Tabular View and a Circular View; here, both the Tabular and Circular views are visualizing a VCF file of translocations in an SKBR3 cancer genome called using Sniffles [18].”
A chromosome-level genome assembly for the Pacific oyster Crassostrea gigas (2020, positive): “gigas genome, structural variants were called with Sniffles (Sniffles, RRID:SCR 017619) [60], after alignment of the PacBio raw reads with ngmlr v0.”
New strategies to improve minimap2 alignment accuracy (2021, methodology): “SVs were called with “snifﬂes -q 10” (Sedlazeck et al., 2018) and compared to the simulated truth with “SURVIVOR eval call.vcf truth.bed 50”.”
Nanopore sequencing technology, bioinformatics and applications (2021, methodology): “A few SV detection tools have been developed (for example, NanoSV 112 , Sniffles 98 , Picky 33 and NanoVar 113 ) (Fig.”
Long-read human genome sequencing and its applications (2020, neutral): “Accompanying this increase in sensitivity has been a spate of new structural variant callers (SMRT-SV 33 , MsPAC 93 , Phased-SV 9 , Sniffles 97 and PBSV 53 ) designed to discover, sequence and, in some cases, phase structural variants on the basis of specific long-read sequence signatures and local ”
Structural variant calling: the long and the short of it (2019, methodology): “SVs are typically described as single events, although more complex scenarios involving combinations of SV types exist [5, 6].”
Nanopore sequencing and assembly of a human genome with ultra-long reads (2017, neutral): “Nanopore reads were aligned back to the assembly using NGM-LR (CoNvex Gap-cost alignMents for Long Reads) 38 and the combined VCF file used for phasing.”
Detection of mosaic and population-level structural variants with Sniffles2 (2024, positive): “This also requires more efficient software to not just detect SVs but also to merge and produce a fully genotyped variant call format (VCF) file 28,29 .”
Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome (2019, methodology): “Sniffles v.1.0.10 was run on pbmm2 CCS reads alignments with -s 3 --skip_ parameter_estimation and with the variant sequence obtained from reads.”
Automated assembly scaffolding elevates a new tomato system for high-throughput genome editing (2021, neutral): “10, max_dist=500 spec_reads=5 --output_genotypes) [35,36].”
Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing (2019, methodology): “PBHoney-NGM used in this study is a modification of PBHoney, that uses the NGM-LR long read aligner (v0.”