Evidence map›Paper›PMID 30235838›Full record

ArticleGenes2018

A Statistical Method for Observing Personal Diploid Methylomes and Transcriptomes with Single-Molecule Real-Time Sequencing.

Yuta Suzuki, Yunhao Wang, Kin Fai Au, Shinichi Morishita

Abstract read
In one paragraph

Article in Genes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. [Clinical diagnostic techniques for rare genetic diseases in children: current status, advances, and thoughts].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2023
    Article
  3. 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

4 authors.

Yuta SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 277-8561, Japan. yuta_suzuki@edu.k.u-tokyo.ac.jp.ORCID 0000-0002-8528-9418
Yunhao WangDepartment of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA. yunhaowang@126.com.ORCID 0000-0002-6949-290X
Kin Fai AuDepartment of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA. kinfai.au@osumc.edu.
Shinichi MorishitaDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 277-8561, Japan. moris@edu.k.u-tokyo.ac.jp.ORCID 0000-0002-6201-8885

Funding

Bioinformatics platform for Hybrid-Seq transcriptome data analysisR01HG008759 · NHGRI · UNIVERSITY OF IOWA · PI AU, KIN FAI · 2016 to 2020
$1.9M
Japan Agency for Medical Research and Development GRIFINJapan Science and Technology Agency CREST JPMJCR13W3Japan Society for the Promotion of Science Grant-in-Aid for JSPS Fellows 15J03645National Human Genome Research Institute R01HG008759NHGRI NIH HHS R01 HG008759Pharmaceutical Research and Manufacturers of America Research Starter Grant (Informatics)University of Iowa Dept. of Internal Medicine, Institutional Fund
6 · The paper itself

Abstract

We address the problem of observing personal diploid methylomes, CpG methylome pairs of homologous chromosomes that are distinguishable with respect to phased heterozygous variants (PHVs), which is challenging due to scarcity of PHVs in personal genomes. Single molecule real-time (SMRT) sequencing is promising as it outputs long reads with CpG methylation information, but a serious concern is whether reliable PHVs are available in erroneous SMRT reads with an error rate of ∼15%. To overcome the issue, we propose a statistical model that reduces the error rate of phasing CpG site to 1%, thereby calling CpG hypomethylation in each haplotype with >90% precision and sensitivity. Using our statistical model, we examined

Indexed as

allele-specific analysisDNA methylationgene expressionsingle molecule real-time sequencingstatistical methods

Identifiers

PMID30235838
PMCPMC6162384

What OpenQuestion holds

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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.