Noninvasive prenatal test (NIPT) has become a routine screening method to detect autosomal chromosomal aberrations. Predicting sex chromosome aneuploidies (SCAs) is more difficult due to the complicated genomic charac...
详细信息
ISBN:
(数字)9798350375749
ISBN:
(纸本)9798350375756
Noninvasive prenatal test (NIPT) has become a routine screening method to detect autosomal chromosomal aberrations. Predicting sex chromosome aneuploidies (SCAs) is more difficult due to the complicated genomic characteristics of sex chromosomes. Benchmarking the sensitivity of NIPT algorithms is challenging due to the lack of positive samples. In this paper, we introduce simple and efficient computational methods to create aberrations on sex chromosomes for NIPT male samples (i.e., creating male samples with XXY or XYY aberrations) from negative NIPT samples. We applied the methods to create 513 positive samples with XXY aberrations and 200 positive samples with XYY aberrations to evaluate the sensitivity of three NIPT algorithms WisecondorX, its improvement VINIPT, and CNVkit. Experiements on both negative and positive samples showed that the algorithms have high sensitivity in detecting XXY and XYY aberrations (100% for WisecondorX and VINIPT; and 99.2% for CNVkit). The VINIPT algorithm has an overall specificity of 99.8% and better than WisecondorX (∼96.8%) and CNVkit (∼99%). The results indicate that VINIPT can play as a powerful tool for screening aberrations on sex chromosomes of male samples.
Noninvasive prenatal test (NIPT) has been widely used for screening trisomy on chromosomes 13 (T13), 18 (T18), and 21 (T21). However, the false negative rate of NIPT algorithms has not been thoroughly evaluated due to...
详细信息
ISBN:
(数字)9798350375749
ISBN:
(纸本)9798350375756
Noninvasive prenatal test (NIPT) has been widely used for screening trisomy on chromosomes 13 (T13), 18 (T18), and 21 (T21). However, the false negative rate of NIPT algorithms has not been thoroughly evaluated due to the lack of positive samples. In this study, we present an efficient computational approach to create positive samples with autosomal trisomy from negative samples. We applied the approach to establish a low coverage dataset of 1440 positive samples with T13, T18, and T21 aberrations for both mosaic and non-mosaic conditions. We examined the performance of WisecondorX and its improvement, called VINIPT, on both negative and positive datasets. Experiments showed that WisecondorX and VINIPT were able to detect all non-mosaic samples with T13, T18, and T21 aberrations (i.e., the sensitivity of 100%). When analyzing mosaic samples, both WisecondorX and VINIPT have the overall sensitivity of 99.7% on detecting T13, T18, and T21 aberrations from mosaic samples. WisecondorX has the specificity of 98.5% for the nonmosaic analysis, but a considerably lower specificity of 95% for the mosaic analysis. VINIPT has a much better specificity than WisecondorX, i.e., 99.9% for the non-mosaic analysis, and 98.2% for the mosaic analysis. The results suggest that VINIPT can play as a powerful tool for detecting autosomal trisomy from the low coverage data.
A genomic database of all Earth’s eukaryotic species could contribute to many scientific discoveries;however, only a tiny fraction of species have genomic information available. In 2018, scientists across the world u...
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