Weighted minimizer sampling improves long read mapping

Jain, Chirag; Rhie, Arang; Zhang, Haowen; Chu, Claudia; Koren, Sergey; Phillippy, Adam M.

doi:10.1101/2020.02.11.943241

Cited by 49 publications

(97 citation statements)

References 41 publications

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“…Nevertheless, post-processing using DuploMap achieved a higher recall (0.906) while maintaining a high precision (0.9954). We also evaluated Winnowmap ( 24 ), a long-read alignment tool that uses a weighted sampling-based method for selecting minimizers to improve long-read mapping using Minimap2 in long tandem repeats. However, Winnowmap’s recall and precision in Long-SegDups regions were lower than those for Minimap2 ( Supplementary Figure S3 ).…”

Section: Resultsmentioning

confidence: 99%

“…Recent work has shown that the accuracy of long-read mapping in extra-long tandem repeats in the human genome—typically found in centromeres—can be improved using specialized computational methods ( 23–25 ) that are designed to exploit the sequence and structure of long repeats. For example, the Winnowmap algorithm ( 24 ) modifies the sequence matching algorithm to avoid filtering out repeated k -mers that are common in tandem repeats ( 24 ).…”

Section: Introductionmentioning

confidence: 99%

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Sensitive alignment using paralogous sequence variants improves long-read mapping and variant calling in segmental duplications

Prodanov

Bansal

2020

Nucleic Acids Research

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The ability to characterize repetitive regions of the human genome is limited by the read lengths of short-read sequencing technologies. Although long-read sequencing technologies such as Pacific Biosciences (PacBio) and Oxford Nanopore Technologies can potentially overcome this limitation, long segmental duplications with high sequence identity pose challenges for long-read mapping. We describe a probabilistic method, DuploMap, designed to improve the accuracy of long-read mapping in segmental duplications. It analyzes reads mapped to segmental duplications using existing long-read aligners and leverages paralogous sequence variants (PSVs)—sequence differences between paralogous sequences—to distinguish between multiple alignment locations. On simulated datasets, DuploMap increased the percentage of correctly mapped reads with high confidence for multiple long-read aligners including Minimap2 (74.3–90.6%) and BLASR (82.9–90.7%) while maintaining high precision. Across multiple whole-genome long-read datasets, DuploMap aligned an additional 8–21% of the reads in segmental duplications with high confidence relative to Minimap2. Using DuploMap-aligned PacBio circular consensus sequencing reads, an additional 8.9 Mb of DNA sequence was mappable, variant calling achieved a higher F1 score and 14 713 additional variants supported by linked-read data were identified. Finally, we demonstrate that a significant fraction of PSVs in segmental duplications overlaps with variants and adversely impacts short-read variant calling.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sensitive alignment using paralogous sequence variants improves long-read mapping and variant calling in segmental duplications

Prodanov

Bansal

2020

Nucleic Acids Research

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“…The total length of HumanGenome after compressing all homopolymer runs is 2,133,004,165. The chrX dataset was generated by mapping the T2T dataset to HumanGenome using Winnowmap (Jain, 2020) and selecting reads that mapped to chrX. In rare cases when a read maps to multiple nearly identical instances of a repeat, Winnowmap…”

Section: Appendicesmentioning

confidence: 99%

LJA: Assembling Long and Accurate Reads Using Multiplex de Bruijn Graphs

Bzikadze

Kolmogorov

Antipov³

et al. 2020

Preprint

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Although the de Bruijn graphs represent the basis of many genome assemblers, it remains unclear how to construct these graphs for large genomes and large k-mer sizes. This algorithmic challenge has become particularly important with the emergence of long and accurate high-fidelity (HiFi) reads that were recently utilized to generate a semi-manual telomere-to-telomere assembly of the human genome using the alternative string graph assembly approach. To enable fully automated high-quality HiFi assemblies of various genomes, we developed an efficient jumboDB algorithm for constructing the de Bruijn graph for large genomes and large k-mer sizes and the LJA genome assembler that error-corrects HiFi reads and uses jumboDB to construct the de Bruijn graph on the error-corrected reads. Since the de Bruijn graph constructed for a fixed k-mer size is typically either too tangled or too fragmented, LJA uses a new concept of a multiplex de Bruijn graph with varying k-mer sizes. We demonstrate that LJA produces contiguous assemblies of complex repetitive regions in genomes including automated assemblies of various highly-repetitive human centromeres.

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“…Nevertheless, post-processing using DuploMap achieved a higher recall (0.906) while maintaining a high precision (0.9954). We also evaluated Winnowmap [24], a long-read alignment tool that uses a weighted sampling based method for selecting minimizers to improve long-read mapping using Minimap2 in long tandem repeats. However, Winnowmap's recall and precision in Long-SegDups regions were lower than those for Minimap2 (Supp.…”

Section: Evaluation Of Mapping Accuracy Using Simulated Readsmentioning

confidence: 99%

“…Long repeated sequences in the human genome result in multiple locations with high scores and pose problems for long-read alignment tools. Recent work has shown that the accuracy of long-read mapping in extra-long tandem repeats in the human genome -typically found in centromeres -can be improved using specialized computational methods [23,24,25] that are designed to exploit the sequence and structure of long repeats. For example, the Winnowmap algorithm [24] modifies the sequence matching algorithm to avoid filtering out repeated k-mers that are common in tandem repeats [24].…”

Section: Introductionmentioning

confidence: 99%

Sensitive alignment using paralogous sequence variants improves long read mapping and variant calling in segmental duplications

Prodanov

Bansal

2020

Preprint

View full text Add to dashboard Cite

The ability to characterize repetitive regions of the human genome is limited by the read lengths of short-read sequencing technologies. Although long-read sequencing technologies such as Pacific Biosciences and Oxford Nanopore can potentially overcome this limitation, long segmental duplications with high sequence identity pose challenges for long-read mapping. We describe a probabilistic method, DuploMap, designed to improve the accuracy of long read mapping in segmental duplications. It analyzes reads mapped to segmental duplications using existing long-read aligners and leverages paralogous sequence variants (PSVs) – sequence differences between paralogous sequences – to distinguish between multiple alignment locations. On simulated datasets, Duplomap increased the percentage of correctly mapped reads with high confidence for multiple long-read aligners including Minimap2 (74.3% to 90.6%) and BLASR (82.9% to 90.7%) while maintaining high precision. Across multiple whole-genome long-read datasets, DuploMap aligned an additional 8-21% of the reads in segmental duplications with high confidence relative to Minimap2. Using Duplomap aligned PacBio CCS reads, an additional 8.9 Mbp of DNA sequence was mappable, variant calling achieved a higher F1-score and 14,713 additional variants supported by linked-read data were identified. Finally, we demonstrate that a significant fraction of PSVs in segmental duplications overlap with variants and adversely impact short-read variant calling.

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Weighted minimizer sampling improves long read mapping

Cited by 49 publications

References 41 publications

Sensitive alignment using paralogous sequence variants improves long-read mapping and variant calling in segmental duplications

Sensitive alignment using paralogous sequence variants improves long-read mapping and variant calling in segmental duplications

LJA: Assembling Long and Accurate Reads Using Multiplex de Bruijn Graphs

Sensitive alignment using paralogous sequence variants improves long read mapping and variant calling in segmental duplications

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