ArticleGigaScience2020
PhaseME: Automatic rapid assessment of phasing quality and phasing improvement.
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.
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Who cites it
11 citing papers in PubMed.
- A novel method for across-chromosome phasing without relative data.Bioinformatics (Oxford, England) · 2026Article
- Article
- Interplay of the Genetic Variants and Allele Specific Methylation in the Context of a Single Human Genome Study.International journal of molecular sciences · 2025Article
- Computational analysis of DNA methylation from long-read sequencing.Nature reviews. Genetics · 2025Review
- The additional diagnostic yield of long-read sequencing in undiagnosed rare diseases.Genome research · 2025Review
- The GIAB genomic stratifications resource for human reference genomes.Nature communications · 2024Article
- Closing the gap: Solving complex medically relevant genes at scale.medRxiv : the preprint server for health sciences · 2024Article
- LRTK: a platform agnostic toolkit for linked-read analysis of both human genome and metagenome.GigaScience · 2024Article
- Towards population-scale long-read sequencing.Nature reviews. Genetics · 2021Review
- An international virtual hackathon to build tools for the analysis of structural variants within species ranging from coronaviruses to vertebrates.F1000Research · 2021Article
- Article
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Authors and funding
2 authors.
Funding
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.
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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.