Evidence map›Paper›PMID 42179192›Full record

ArticleJournal of clinical laboratory analysis2026

In Silico Fragment Size Selection for Enhanced Fetal Fraction and Abnormality Origin Discernment Using Pair-End Sequencing of Maternal Plasma DNA.

Lihui Yang, Jiutong Zhang, Ji Zhang, Qiujie Jin, Yating Wang, Qiuhua Wu, Fengrui Shi, Rui Wang, Yunping Liu, Na Cai and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical laboratory analysis, 2026. 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

12 authors.

Lihui YangCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.
Jiutong ZhangBerry Genomics Corporation, Beijing, China.
Ji ZhangBerry Genomics Corporation, Beijing, China.ORCID https://orcid.org/0009-0000-9409-4324
Qiujie JinCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.
Yating WangCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.
Qiuhua WuCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.
Fengrui ShiCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.
Rui WangCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.
Yunping LiuBerry Genomics Corporation, Beijing, China.
Na CaiCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.
Xiaobin WangCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.
Rong QiangCenter of Neonatal Disease Screening, Department of Clinical Genetics, Northwest Women's and Children's Hospital, Xi'an, China.

Funding

Shaanxi Provincial Health Research Innovation Capability Enhancement Program - Platform Construction Project 2024PT-03Shaanxi Provincial Key Research and Development Plan: Major Industrial Innovation Chain (Group) Project 2024SF-ZDCYL-04-05
6 · The paper itself

Abstract

objectivesThe aim of this study was to develop and evaluate a new bioinformatics pipeline that improves fetal DNA fraction (FF), determines the origin of chromosomal abnormalities, and better detects sex chromosomal aneuploidies (SCAs) than routine NIPT.

methodsWe used a bioinformatic strategy that filters out longer DNA fragments, thereby significantly improving the FF. By combining the filtered data with the original data, we determined the origin of detected abnormalities.

resultsWe analyzed samples from 204 pregnancies. Using routing NIPT methods, 36 samples were negative, 37 exhibited low FF, and 131 were detected as positive. Applying the method of this study, all the low FF samples were qualified for analysis. Furthermore, 56 samples initially classified as positive were identified to be false positives, predominantly caused by maternal abnormalities. No false negative results were observed with this method.

conclusionWe developed a pipeline for NIPT that significantly improves FF, which helps deduce the origin of abnormalities and detect more karyotypes of SCAs. The strategy has the potential to improve the specificity of NIPT.

Indexed as

DNAFetusPrenatal DiagnosisSequence Analysis, DNAAneuploidyComputational BiologyComputer SimulationFemaleHumansPregnancyDNAcopy number variationsfetal DNA fractionnoninvasive prenatal testingpair‐end sequencingsex chromosomal aneuploidy

Identifiers

PMID42179192
PMCPMC13371283

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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.