Exploring single-sample SNP and INDEL calling with whole-genome de novo assembly

By Heng Li. Bioinform., 2012

425 citations recorded by the source corpus.

MOTIVATION Eugene Myers in his string graph paper suggested that in a string graph or equivalently a unitig graph, any path spells a valid assembly. As a string/unitig graph also encodes every valid assembly of reads, such a graph, provided that it can be constructed correctly, is in fact a lossless representation of reads. In principle, every analysis based on whole-genome shotgun sequencing (WGS) data, such as SNP and insertion/deletion (INDEL) calling, can also be achieved with unitigs. RESULTS To explore the feasibility of using de novo assembly in the context of resequencing, we developed a de novo assembler, fermi, that assembles Illumina short reads into unitigs while preserving most of information of the input reads. SNPs and INDELs can be called by mapping the unitigs against a reference genome. By applying the method on 35-fold human resequencing data, we showed that in comparison to the standard pipeline, our approach yields similar accuracy for SNP calling and better results for INDEL calling. It has higher sensitivity than other de novo assembly based methods for variant calling. Our work suggests that variant calling with de novo assembly can be a beneficial complement to the standard variant calling pipeline for whole-genome resequencing. In the methodological aspects, we propose FMD-index for forward-backward extension of DNA sequences, a fast algorithm for finding all super-maximal exact matches and one-pass construction of unitigs from an FMD-index. AVAILABILITY http://github.com/lh3/fermi

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/21715c032e869a57a473bfc0869b762339852198

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Citations in the corpus

Assembling the 20 Gb white spruce (Picea glauca) genome from whole-genome shotgun sequencing data (2013, methodology): “Assembly execution times are given in Supplementary Table S1.”
Toward better understanding of artifacts in variant calling from high-coverage samples (2014, methodology): “…variant calls from different pipelines, or by comparing calls to variants ascertained with array genotyping or in another study (Clark et al., 2011; Li, 2012; Lam et al., 2012a,b; Boland et al., 2013; Liu et al., 2013; Goode et al., 2013; O’Rawe et al., 2013; Zook et al., 2014; Cheng et al., 2014).”
Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences (2015, methodology): “Fermi (Li, 2012) uses a similar algorithm except that it keeps two optimal paths through the bubble.”
Efficient Architecture-Aware Acceleration of BWA-MEM for Multicore Systems (2019, methodology): “An SMEM is a MEM that is not contained in any other MEMs on the query sequence [12].”
Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species (2013, methodology): “More recent assemblers such as SGA [11] and fermi [12] have capitalized on the increasing length of sequence reads, and utilize string graph approaches, recalling the previous generation of overlap-layout-consensus assemblers.”
An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge (2014, methodology): “Eight groups analyzed only the SOLiD WES data and four restricted their analysis to the Complete Genomics WGS data, often because of real or perceived difficulties with converting the extensible sequence format from the SOLiD runs into generic FASTQ files that would run on BWA, or unfamiliarity with”
Musket: a multistage k-mer spectrum-based error corrector for Illumina sequence data (2013, methodology): “Furthermore, some recent assemblers, such as SGA (Simpson and Durbin, 2012) and Fermi (Li, 2012), have used string graphs.”