Evidence mapPaperPMID 39389018Full record

ArticleCell genomics2024

Utilizing non-invasive prenatal test sequencing data for human genetic investigation.

Siyang Liu, Yanhong Liu, Yuqin Gu, Xingchen Lin, Huanhuan Zhu, Hankui Liu, Zhe Xu, Shiyao Cheng, Xianmei Lan, Linxuan Li and 9 more

Abstract read
In one paragraph

Article in Cell genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 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

19 authors.

Siyang LiuSchool of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China; Shenzhen Key Laboratory of Pathogenic Microbes and Biosafety, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China; BGI-Shenzhen, Shenzhen 518083, Guangdong, China; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. Electronic address: liusy99@mail.sysu.edu.cn.
Yanhong LiuSchool of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.
Yuqin GuSchool of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.
Xingchen LinSchool of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.
Huanhuan ZhuBGI-Shenzhen, Shenzhen 518083, Guangdong, China.
Hankui LiuBGI Genomics, BGI-Shenzhen, Shenzhen 518083, Guangdong, China.
Zhe XuDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Shiyao ChengSchool of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China; Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Xianmei LanBGI-Shenzhen, Shenzhen 518083, Guangdong, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
Linxuan LiBGI-Shenzhen, Shenzhen 518083, Guangdong, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
Mingxi HuangDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China.
Hao LiDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Rasmus NielsenDepartment of Integrative Biology, University of California, Berkeley, Berkeley, CA 94720, USA.
Robert W DaviesDepartment of Statistics, University of Oxford, Oxford, UK.
Anders AlbrechtsenBioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark.
Guo-Bo ChenCenter for Productive Medicine, Department of Genetic and Genomic Medicine, Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.
Xiu QiuDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China; Provincial Clinical Research Center for Child Health, Guangzhou 510623, China; Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China.
Xin JinBGI-Shenzhen, Shenzhen 518083, Guangdong, China; The Innovation Centre of Ministry of Education for Development and Diseases, School of Medicine, South China University of Technology, Guangzhou 510006, Guangdong, China; Shanxi Medical University-BGI Collaborative Center for Future Medicine, Shanxi Medical University, Taiyuan 030001, China; Shenzhen Key Laboratory of Transomics Biotechnologies, BGI Research, Shenzhen 518083, China. Electronic address: jinxin@genomics.cn.
Shujia HuangBGI-Shenzhen, Shenzhen 518083, Guangdong, China; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. Electronic address: shujia.huang@bigcs.org.

Funding

Inference and application of graphs for genomic dataR35GM153400 · UNIVERSITY OF CALIFORNIA BERKELEY · 2025 to 2025
$427k
NIGMS NIH HHS R35 GM153400
6 · The paper itself

Abstract

Non-invasive prenatal testing (NIPT) employs ultra-low-pass sequencing of maternal plasma cell-free DNA to detect fetal trisomy. Its global adoption has established NIPT as a large human genetic resource for exploring genetic variations and their associations with phenotypes. Here, we present methods for analyzing large-scale, low-depth NIPT data, including customized algorithms and software for genetic variant detection, genotype imputation, family relatedness, population structure inference, and genome-wide association analysis of maternal genomes. Our results demonstrate accurate allele frequency estimation and high genotype imputation accuracy (R

Indexed as

Genome-Wide Association StudyAlgorithmsFemaleGene FrequencyGenotypeHumansNoninvasive Prenatal TestingPolymorphism, Single NucleotidePregnancyPrenatal DiagnosisSequence Analysis, DNASoftwareallele frequency estimationcell-free DNAfamily relatednessgenome-wide association analysisgenotype imputationlow-pass whole-genome sequencingNIPT-human-genetics workflownon-invasive prenatal testpopulation structurevariant detection

Identifiers

PMID39389018
PMCPMC11602596

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.