FF-QuantSC: accurate quantification of fetal fraction by a neural network model.
Mol Genet Genomic Med
; 8(6): e1232, 2020 06.
Article
em En
| MEDLINE
| ID: mdl-32281746
ABSTRACT
BACKGROUND:
Noninvasive prenatal testing (NIPT) is one of the most commonly employed clinical measures for screening of fetal aneuploidy. Fetal Fraction (ff) has been demonstrated to be one of the key factors affecting the performance of NIPT. Accurate quantification of ff plays vital role in NIPT.METHODS:
In this study, we present a new approach, the accurate Quantification of Fetal Fraction with Shallow-Coverage sequencing of maternal plasma DNA (FF-QuantSC), for the estimation of ff in NIPT. The method employs neural network model and utilizes differential genomic patterns between fetal and maternal genomes to quantify ff.RESULTS:
Our results show that the predicted ff by FF-QuantSC exhibit high correlation with the Y chromosome-based method on male pregnancies, and achieves the highest accuracy compared with other ff estimation approaches. We also demonstrate that the model generates statistically similar results on both male and female pregnancies.CONCLUSION:
FF-QuantSC achieves high accuracy in ff quantification. The method is suitable for application in both male and female pregnancies. Since the method does not require additional information upon NIPT routines, it can be easily incorporated into current NIPT settings without causing extra costs. We believe that FF-QuantSC shall provide valuable additions to NIPT.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Redes Neurais de Computação
/
Análise de Sequência de DNA
/
Teste Pré-Natal não Invasivo
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Adult
/
Female
/
Humans
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Pregnancy
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article