Accurate chromosome-scale haplotype-resolved assembly of human genomes

Garg, Shilpa; Fungtammasan, Arkarachai; Carroll, Andrew; Chou, Mike; Schmitt, Anthony; Zhou, Xiang; Mac, Stephen; Peluso, Paul; Hatas, Emily; Ghurye, Jay; Maguire, Jared; Mahmoud, Medhat; Cheng, Haoyu; Heller, David; Zook, Justin M.; Moemke, Tobias; Marschall, Tobias; Sedlazeck, Fritz J.; Aach, John; Chin, Chen-Shan; Church, George M.; Li, Heng

doi:10.1101/810341

Cited by 37 publications

(63 citation statements)

References 24 publications

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“…Although we use the Genome in a Bottle set as the primary reference set of variants for benchmarking SVs, another study has published an independently derived set of high quality SVs in the same HG002 individual [ 11 ]. As a post-hoc analysis, we used Truvari to determine whether any of the so-called GIAB relative false positives from the three pipelines were found to be true positives against this call set.…”

Section: Discussionmentioning

confidence: 99%

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Leveraging a WGS compression and indexing format with dynamic graph references to call structural variants

English¹,

McCarthy²,

Flickenger³

et al. 2020

Preprint

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We introduce a novel structural variant calling pipeline (BioGraph) that leverages a read compression and indexing format to discover alleles, assess their supporting coverage, and assign useful quality scores. To evaluate BioGraph's performance, we run five sequencing replicates of the individual HG002 through the BioGraph variant calling pipeline, as well as two other short-read sv-calling pipelines. BioGraph detects the GIAB benchmark SVs at a peak sensitivity of ≈59% compared to ≈42% sensitivity from the other pipelines. The overall precision of BioGraph is lower than other pipelines (≈81% and ≈90%, respectively), however, adjusting for quality score, BioGraph calls were sensitive to a greater number of SV calls given the same false discovery rate compared to the other pipelines. Cumulatively ≈77% of GIAB benchmark SVs are discovered by BioGraph in at least one replicate. After merging discovered calls and running BioGraph Coverage to create a squared-off project-level VCF, we find ≈90% percent of discovered true positive alleles have at least 5x coverage in all replicates, thus increasing per-replicate recall of alleles having at least 1x coverage to ≈76.9%.

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Section: Discussionmentioning

confidence: 99%

“…The exhaustive, global search for assembly paths relative to a reference performed by [ 22 ], with each allele's true positive or false positive state assigned based on the comparison of haplotype-resolved assemblies of long-reads for HG002 [ 11 ] against the GIAB v0.6 Tier 1 set using Turvari.…”

Section: Biograph Qualclassifiermentioning

confidence: 99%

Leveraging a WGS compression and indexing format with dynamic graph references to call structural variants

English¹,

McCarthy²,

Flickenger³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Additionally, single nucleotide variants were called at comparable precision and recall to Illumina ® NovaSeq ™ data. Since the initial publication, greatly improved assembly results have been observed in other human sequencing projects [22][23][24][25] .…”

Section: Background and Summarymentioning

confidence: 99%

Highly accurate long-read HiFi sequencing data for five complex genomes

Hon

Mars

Young

et al. 2020

Preprint

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The PacBio ® HiFi sequencing method yields highly accurate long-read sequencing datasets with read lengths averaging 10-25 kb and accuracies greater than 99.5%. These accurate long reads can be used to improve results for complex applications such as single nucleotide and structural variant detection, genome assembly, assembly of difficult polyploid or highly repetitive genomes, and assembly of metagenomes. Currently, there is a need for sample data sets to both evaluate the benefits of these long accurate reads as well as for development of bioinformatic tools including genome assemblers, variant callers, and haplotyping algorithms. We present deep coverage HiFi datasets for five complex samples including the two inbred model genomes Mus musculus and Zea mays, as well as two complex genomes, octoploid Fragaria × ananassa and the diploid anuran Rana muscosa. Additionally, we release sequence data from a mock metagenome community. The datasets reported here can be used without restriction to develop new algorithms and explore complex genome structure and evolution. Data were generated on the PacBio Sequel II System.

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“…For CHM13, the assembly was generated using Canu on 24x PacBio HiFi data 9 . The assemblies for HG002 and NA12878 were generated using Peregrine 21 on~30x PacBio HiFi and then scaffolded using HiRise/3d-dna on ~30x Hi-C data 22 .…”

Section: Human Genome Assembliesmentioning

confidence: 99%

SDip: A novel graph-based approach to haplotype-aware assembly based structural variant calling in targeted segmental duplications sequencing

Heller

Vingron

Church

et al. 2020

Preprint

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Segmental duplications are important for understanding human diseases and evolution. The challenge to distinguish allelic and duplication sequences has hindered their phased assembly as well as characterization of structural variant calls. Here we have developed a novel graph-based approach that leverages single nucleotide differences in overlapping reads to distinguish allelic and duplication sequences information from long read accurate PacBio HiFi sequencing. These differences enable to generate allelic and duplication-specific overlaps in the graph to spell out phased assembly used for structural variant calling. We have applied our method to three public genomes: CHM13, NA12878 and HG002. Our method resolved 86% of duplicated regions fully with contig N50 up to 79 kb and produced <800 structural variant phased calls, outperforming state-of-the-part SDA method in terms of all metrics. Furthermore, we demonstrate the importance of phased assemblies and variant calls to the biologically-relevant duplicated genes such as SMN1, SRGAP2C, NPY4R and FAM72A. Our phased assemblies and accurate variant calling specifically in duplicated regions will enable the study of the evolution and adaptation of various species.

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Accurate chromosome-scale haplotype-resolved assembly of human genomes

Cited by 37 publications

References 24 publications

Leveraging a WGS compression and indexing format with dynamic graph references to call structural variants

Leveraging a WGS compression and indexing format with dynamic graph references to call structural variants

Highly accurate long-read HiFi sequencing data for five complex genomes

SDip: A novel graph-based approach to haplotype-aware assembly based structural variant calling in targeted segmental duplications sequencing

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