Evidence map›Paper›PMID 38632226›Full record

ArticleHuman genome variation2024

Comparative evaluation of SNVs, indels, and structural variations detected with short- and long-read sequencing data.

Shunichi Kosugi, Chikashi Terao

Abstract read
In one paragraph

Article in Human genome variation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Long-read sequencing for neurological disorders: opportunities, challenges, and future directions.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
    Review
  5. DNA Replication Errors Drive Genome-Wide Small Inverted Triplication Dynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
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  12. Article
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  14. Article
  15. Article
  16. Review
  17. Neurofibromin 1 (International journal of molecular sciences · 2026
    Article
  18. Article
  19. Article
  20. 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.

Shunichi KosugiCenter for Genome Informatics, Research Organization of Information and Systems, Joint Support-Center for Data Science Research, Shizuoka, Japan. shunichi.kosugi@nig.ac.jp.
Chikashi TeraoLaboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.

Funding

MEXT | Japan Society for the Promotion of Science (JSPS) JP17K07264
6 · The paper itself

Abstract

Short- and long-read sequencing technologies are routinely used to detect DNA variants, including SNVs, indels, and structural variations (SVs). However, the differences in the quality and quantity of variants detected between short- and long-read data are not fully understood. In this study, we comprehensively evaluated the variant calling performance of short- and long-read-based SNV, indel, and SV detection algorithms (6 for SNVs, 12 for indels, and 13 for SVs) using a novel evaluation framework incorporating manual visual inspection. The results showed that indel-insertion calls greater than 10 bp were poorly detected by short-read-based detection algorithms compared to long-read-based algorithms; however, the recall and precision of SNV and indel-deletion detection were similar between short- and long-read data. The recall of SV detection with short-read-based algorithms was significantly lower in repetitive regions, especially for small- to intermediate-sized SVs, than that detected with long-read-based algorithms. In contrast, the recall and precision of SV detection in nonrepetitive regions were similar between short- and long-read data. These findings suggest the need for refined strategies, such as incorporating multiple variant detection algorithms, to generate a more complete set of variants using short-read data.

Identifiers

PMID38632226
PMCPMC11024196

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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.