Evidence map›Paper›PMID 40526493›Full record

ArticleGigaScience2025

PISAD: reference-free intraspecies sample anomalies detection tool based on k-mer counting.

Zhantian Xu, Fan Nie, Jianxin Wang

Abstract read
In one paragraph

Article in GigaScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Zhantian XuSchool of Computer Science and Engineering, Central South University, Changsha 410083, China.ORCID 0009-0001-7237-8112
Fan NieNational Center for Applied Mathematics in Hunan and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Hunan 411105, China.ORCID 0009-0002-9172-0822
Jianxin WangSchool of Computer Science and Engineering, Central South University, Changsha 410083, China.ORCID 0000-0003-1516-0480

Funding

National Natural Science Foundation of China 62332020National Natural Science Foundation of China 62350004Project of Xiangjiang Laboratory No. 23XJ01011Xinjiang Uygur Autonomous Region Key R & D program No. 2024B03039-3
6 · The paper itself

Abstract

backgroundGenomic sequencing research often requires the simultaneous analysis of heterogeneous data types across single or multiple individuals, introducing a substantial risk of sample swaps (e.g., labeling errors). Existing methods primarily rely on reference information, requiring the preselection of informative variant sites with a population allele frequency around 0.5, which may be insufficient or unavailable for nonmodel organisms. As research expands to encompass a growing number of new species, a robust quality control tool will become increasingly important. FINDS: We developed PISAD (Phased Intraspecies Sample Anomalies Detection), a tool for validating sample identities in whole-genome sequencing (WGS) data without requiring reference information. It uses a 2-stage approach: first, it performs rapid, reference-free single nucleotide polymorphism (SNP) calling on low-error-rate data from the target individual to create a variant sketch; then, it assesses the concordance of other samples on this sketch to verify relationships. We assessed the performance and efficiency of PISAD on Homo sapiens, Bos taurus, Gallus gallus, Arctia plantaginis, and Pyrus species.

conclusionsOur evaluation showed that PISAD achieves a lower data coverage requirement (0.5×) compared to the reference-based tool ntsm and is broadly applicable to multiple diploid species.

Indexed as

GenomicsSoftwareWhole Genome SequencingAnimalsCattleHumansPolymorphism, Single Nucleotidek-mer analysisquality controlreference-freesample swapSNP calling

Identifiers

PMID40526493
PMCPMC12202988

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.