Evidence map›Paper›PMID 36766477›Full record

ReviewDiagnostics (Basel, Switzerland)2023

Next-Generation Sequencing (NGS) and Third-Generation Sequencing (TGS) for the Diagnosis of Thalassemia.

Syahzuwan Hassan, Rosnah Bahar, Muhammad Farid Johan, Ezzeddin Kamil Mohamed Hashim, Wan Zaidah Abdullah, Ezalia Esa, Faidatul Syazlin Abdul Hamid, Zefarina Zulkafli

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
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  10. The Molecular Pathology of Non-Malignant Haematological Disease.British journal of biomedical science · 2026
    Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. Molecular Characterization of Three Novel Large Deletions Causing αInternational journal of molecular sciences · 2025
    Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review
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

8 authors.

Syahzuwan HassanDepartment of Hematology, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia.
Rosnah BaharDepartment of Hematology, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia.
Muhammad Farid JohanDepartment of Hematology, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia.ORCID 0000-0001-6344-0220
Ezzeddin Kamil Mohamed HashimSchool of Health Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia.
Wan Zaidah AbdullahDepartment of Hematology, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia.
Ezalia EsaInstitute for Medical Research, Shah Alam 40170, Malaysia.
Faidatul Syazlin Abdul HamidInstitute for Medical Research, Shah Alam 40170, Malaysia.
Zefarina ZulkafliDepartment of Hematology, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia.ORCID 0000-0003-2029-2234

Funding

Ministry of Higher Education FRGS/1/2019/SKK06/USM/02/8
6 · The paper itself

Abstract

Thalassemia is one of the most heterogeneous diseases, with more than a thousand mutation types recorded worldwide. Molecular diagnosis of thalassemia by conventional PCR-based DNA analysis is time- and resource-consuming owing to the phenotype variability, disease complexity, and molecular diagnostic test limitations. Moreover, genetic counseling must be backed-up by an extensive diagnosis of the thalassemia-causing phenotype and the possible genetic modifiers. Data coming from advanced molecular techniques such as targeted sequencing by next-generation sequencing (NGS) and third-generation sequencing (TGS) are more appropriate and valuable for DNA analysis of thalassemia. While NGS is superior at variant calling to TGS thanks to its lower error rates, the longer reads nature of the TGS permits haplotype-phasing that is superior for variant discovery on the homologous genes and CNV calling. The emergence of many cutting-edge machine learning-based bioinformatics tools has improved the accuracy of variant and CNV calling. Constant improvement of these sequencing and bioinformatics will enable precise thalassemia detections, especially for the CNV and the homologous

Indexed as

CNVNGSPCRsequencingTGSthalassemia

Identifiers

PMID36766477
PMCPMC9914462

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.