Evidence map›Paper›PMID 32706368›Full record

ArticleGigaScience2020

PhaseME: Automatic rapid assessment of phasing quality and phasing improvement.

Sina Majidian, Fritz J Sedlazeck

Abstract read
In one paragraph

Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Closing the gap: Solving complex medically relevant genes at scale.medRxiv : the preprint server for health sciences · 2024
    Article
  8. Article
  9. Towards population-scale long-read sequencing.Nature reviews. Genetics · 2021
    Review
  10. Article
  11. Article
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

2 authors.

Sina MajidianSchool of Electrical Engineering, Iran University of Science & Technology, Narmak, Tehran 1684613114, Iran.
Fritz J SedlazeckHuman Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.

Funding

Genomic Architecture of Common Disease in Diverse Populations: WGS of Ongoing Hemorrhagic Stroke Study SupplementUM1HG008898 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GIBBS, RICHARD A · 2016 to 2020
$77.0M
NHGRI NIH HHS UM1 HG008898
6 · The paper itself

Abstract

backgroundThe detection of which mutations are occurring on the same DNA molecule is essential to predict their consequences. This can be achieved by phasing the genomic variations. Nevertheless, state-of-the-art haplotype phasing is currently a black box in which the accuracy and quality of the reconstructed haplotypes are hard to assess.

findingsHere we present PhaseME, a versatile method to provide insights into and improvement of sample phasing results based on linkage data. We showcase the performance and the importance of PhaseME by comparing phasing information obtained from Pacific Biosciences including both continuous long reads and high-quality consensus reads, Oxford Nanopore Technologies, 10x Genomics, and Illumina sequencing technologies. We found that 10x Genomics and Oxford Nanopore phasing can be significantly improved while retaining a high N50 and completeness of phase blocks. PhaseME generates reports and summary plots to provide insights into phasing performance and correctness. We observed unique phasing issues for each of the sequencing technologies, highlighting the necessity of quality assessments. PhaseME is able to decrease the Hamming error rate significantly by 22.4% on average across all 5 technologies. Additionally, a significant improvement is obtained in the reduction of long switch errors. Especially for high-quality consensus reads, the improvement is 54.6% in return for only a 5% decrease in phase block N50 length.

conclusionsPhaseME is a universal method to assess the phasing quality and accuracy and improves the quality of phasing using linkage information. The package is freely available at https://github.com/smajidian/phaseme.

Indexed as

SoftwareComputational BiologyGenomicsHaplotypesHumansMutationPolymorphism, Single NucleotideSequence Analysis, DNAWorkflowbioinformaticsDNA sequencinghaplotype phasingquality assessment

Identifiers

PMID32706368
PMCPMC7379178

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LicenceCC BY
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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.