Adaptable Model Parameters in Non-Invasive Prenatal Testing Lead to More Stable Predictions.
Int J Mol Sci
; 20(14)2019 Jul 11.
Article
en En
| MEDLINE
| ID: mdl-31336782
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.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Diagnóstico Prenatal
/
Modelos Estadísticos
/
Técnicas de Diagnóstico Molecular
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Female
/
Humans
/
Pregnancy
Idioma:
En
Revista:
Int J Mol Sci
Año:
2019
Tipo del documento:
Article
País de afiliación:
Eslovaquia
Pais de publicación:
Suiza