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Adaptable Model Parameters in Non-Invasive Prenatal Testing Lead to More Stable Predictions

Authors :
Juraj Gazdarica
Jaroslav Budis
Frantisek Duris
Jan Turna
Tomas Szemes
Source :
International Journal of Molecular Sciences, Vol 20, Iss 14, p 3414 (2019)
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

Recent advances in massively parallel shotgun sequencing opened up new options for affordable non-invasive prenatal testing (NIPT) for fetus aneuploidy from DNA material extracted from maternal plasma. Tests typically compare chromosomal distributions of a tested sample with a control set of healthy samples with unaffected fetuses. Deviations above certain threshold levels are concluded as positive findings. The main problem with this approach is that the variance of the control set is dependent on the number of sequenced fragments. The higher the amount, the more precise the estimation of actual chromosomal proportions is. Testing a sample with a highly different number of sequenced reads as used in training may thus lead to over- or under-estimation of their variance, and so lead to false predictions. We propose the calculation of a variance for each tested sample adaptively, based on the actual number of its sequenced fragments. We demonstrate how it leads to more stable predictions, mainly in real-world diagnostics with the highly divergent inter-sample coverage.

Details

Language :
English
ISSN :
14220067
Volume :
20
Issue :
14
Database :
Directory of Open Access Journals
Journal :
International Journal of Molecular Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.1d2a5c2d977f471aa7ad1c60e2be39a6
Document Type :
article
Full Text :
https://doi.org/10.3390/ijms20143414