Evidence map›Paper›PMID 27940952›Full record

ArticleGenome research2017

HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies.

Peter Edge, Vineet Bafna, Vikas Bansal

Abstract read
In one paragraph

Article in Genome research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 227 papers.

0numbers the graph read from it
0cells of the map it votes in
227citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

227 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

167 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Peter EdgeDepartment of Computer Science & Engineering, University of California, San Diego, La Jolla, California 92053, USA.
Vineet BafnaDepartment of Computer Science & Engineering, University of California, San Diego, La Jolla, California 92053, USA.
Vikas BansalDepartment of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, California 92053, USA.

Funding

TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
Single-stranded sequencing using microfluidic reactors (SISSOR)R01HG007836 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HUANG, XIAOHUA, ZHANG, KUN · 2014 to 2017
$3.6M
Computational methods for detecting patterns of complex genomic variationR01GM114362 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Vineet Bafna · 2016 to 2026
$3.1M
Methods for detecting short indels from high-throughput sequence dataR21HG007430 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BANSAL, VIKAS · 2013 to 2014
$476k
NHGRI NIH HHS R01 HG007836NHGRI NIH HHS R21 HG007430NIGMS NIH HHS P41 GM103484NIGMS NIH HHS R01 GM114362
6 · The paper itself

Abstract

Many tools have been developed for haplotype assembly-the reconstruction of individual haplotypes using reads mapped to a reference genome sequence. Due to increasing interest in obtaining haplotype-resolved human genomes, a range of new sequencing protocols and technologies have been developed to enable the reconstruction of whole-genome haplotypes. However, existing computational methods designed to handle specific technologies do not scale well on data from different protocols. We describe a new algorithm, HapCUT2, that extends our previous method (HapCUT) to handle multiple sequencing technologies. Using simulations and whole-genome sequencing (WGS) data from multiple different data types-dilution pool sequencing, linked-read sequencing, single molecule real-time (SMRT) sequencing, and proximity ligation (Hi-C) sequencing-we show that HapCUT2 rapidly assembles haplotypes with best-in-class accuracy for all data types. In particular, HapCUT2 scales well for high sequencing coverage and rapidly assembled haplotypes for two long-read WGS data sets on which other methods struggled. Further, HapCUT2 directly models Hi-C specific error modalities, resulting in significant improvements in error rates compared to HapCUT, the only other method that could assemble haplotypes from Hi-C data. Using HapCUT2, haplotype assembly from a 90× coverage whole-genome Hi-C data set yielded high-resolution haplotypes (78.6% of variants phased in a single block) with high pairwise phasing accuracy (∼98% across chromosomes). Our results demonstrate that HapCUT2 is a robust tool for haplotype assembly applicable to data from diverse sequencing technologies.

Indexed as

HaplotypesSoftwareContig MappingGenome, HumanGenomicsHumansSequence Analysis, DNA

Identifiers

PMID27940952
PMCPMC5411775

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.