Evidence map›Paper›PMID 37277343›Full record

ArticleNature communications2023

INSurVeyor: improving insertion calling from short read sequencing data.

Ramesh Rajaby, Dong-Xu Liu, Chun Hang Au, Yuen-Ting Cheung, Amy Yuet Ting Lau, Qing-Yong Yang, Wing-Kin Sung

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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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

24 citing papers in PubMed.

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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

7 authors.

Ramesh RajabyHong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China.
Dong-Xu LiuNational Key Laboratory of Crop Genetic Improvement, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China.
Chun Hang AuHong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China.ORCID 0000-0002-1707-0991
Yuen-Ting CheungHong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China.ORCID 0000-0002-1140-3222
Amy Yuet Ting LauHong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China.
Qing-Yong YangNational Key Laboratory of Crop Genetic Improvement, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China.ORCID 0000-0002-3510-8906
Wing-Kin SungHong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China. kwksung@cuhk.edu.hk.ORCID 0000-0001-7806-7086

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insertions are one of the major types of structural variations and are defined as the addition of 50 nucleotides or more into a DNA sequence. Several methods exist to detect insertions from next-generation sequencing short read data, but they generally have low sensitivity. Our contribution is two-fold. First, we introduce INSurVeyor, a fast, sensitive and precise method that detects insertions from next-generation sequencing paired-end data. Using publicly available benchmark datasets (both human and non-human), we show that INSurVeyor is not only more sensitive than any individual caller we tested, but also more sensitive than all of them combined. Furthermore, for most types of insertions, INSurVeyor is almost as sensitive as long reads callers. Second, we provide state-of-the-art catalogues of insertions for 1047 Arabidopsis Thaliana genomes from the 1001 Genomes Project and 3202 human genomes from the 1000 Genomes Project, both generated with INSurVeyor. We show that they are more complete and precise than existing resources, and important insertions are missed by existing methods.

Indexed as

High-Throughput Nucleotide SequencingSequence Analysis, DNA

Identifiers

PMID37277343
PMCPMC10241795

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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.