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Cost-effective and accurate method of measuring fetal fraction using SNP imputationoa mark
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Publication Year
2018-04-01
Publisher
Oxford University Press
Citation
Bioinformatics, Vol.34, pp.1086-1091
Mesh Keyword
AlgorithmsAllelesCost-Benefit AnalysisData AccuracyDNAFemaleGenotyping TechniquesHumansPolymorphism, Single NucleotidePregnancyPrenatal DiagnosisSequence Analysis, DNA
All Science Classification Codes (ASJC)
Statistics and ProbabilityBiochemistryMolecular BiologyComputer Science ApplicationsComputational Theory and MathematicsComputational Mathematics
Abstract
Motivation With the discovery of cell-free fetal DNA in maternal blood, the demand for non-invasive prenatal testing (NIPT) has been increasing. To obtain reliable NIPT results, it is important to accurately estimate the fetal fraction. In this study, we propose an accurate and cost-effective method for measuring fetal fractions using single-nucleotide polymorphisms (SNPs). Results A total of 84 samples were sequenced via semiconductor sequencing using a 0.3× sequencing coverage. SNPs were genotyped to estimate the fetal fraction. Approximately 900 000 SNPs were genotyped, and 250 000 of these SNPs matched the semiconductor sequencing results. We performed SNP imputation (1000Genome phase3 and HRC v1.1 reference panel) to increase the number of SNPs. The correlation coefficients (R 2) of the fetal fraction estimated using the ratio of non-maternal alleles when coverage was reduced to 0.01 following SNP imputation were 0.93 (HRC v1.1 reference panel) and 0.90 (1000GP3 reference panel). An R 2 of 0.72 was found at 0.01× sequencing coverage with no imputation performed. We developed an accurate method to measure fetal fraction using SNP imputation, showing cost-effectiveness by using different commercially available SNP chips and lowering the coverage. We also showed that semiconductor sequencing, which is an inexpensive option, was useful for measuring fetal fraction. Availability and implementation python source code and guidelines can be found at https://github.com/KMJ403/fetalfraction-SNPimpute. Contact kangskim@ajou.ac.kr or sunshinkim3@gmail.com Supplementary informationSupplementary dataare available at Bioinformatics online.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/30190
DOI
https://doi.org/10.1093/bioinformatics/btx728
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Type
Article
Funding
This research was supported by the MSIP (Ministry of Science, ICT & Future Planning), Korea, under the \u2018Employment Contract based Master\u2019s Degree Program for Information Security\u2019 supervised by the KISA (Korea Internet & Security Agency) (H2101-16-1001).
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KIM, Jai Hoon김재훈
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