Hanli Xu1, Shaowei Wang2, Lin-Lin Ma3, Shuai Huang3, Lin Liang3, Qian Liu4, Yang-Yang Liu4, Ke-Di Liu4,5, Ze-Min Tan4, Hao Ban6,7, Yongtao Guan8,9,10, Zuhong Lu11. 1. Department of Biomedical Engineering, Southeast University, Nanjing, China. 2. Department of Obstetrics and Gynecology, Beijing Hospital, Beijing, China. w_sw999@163.com. 3. Department of Obstetrics and Gynecology, Beijing Hospital, Beijing, China. 4. Beijing USCI Medical Laboratory, Beijing, China. 5. Department of Biochemistry & Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK. 6. USDA/ARS Children's Nutrition Research Center, Houston, Texas, USA. 7. Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA. 8. USDA/ARS Children's Nutrition Research Center, Houston, Texas, USA. yongtaog@bcm.edu. 9. Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA. yongtaog@bcm.edu. 10. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA. yongtaog@bcm.edu. 11. Department of Biomedical Engineering, Southeast University, Nanjing, China. zhlu@seu.edu.cn.
Abstract
PURPOSE: Noninvasive prenatal screening (NIPS) sequences a mixture of the maternal and fetal cell-free DNA. Fetal trisomy can be detected by examining chromosomal dosages estimated from sequencing reads. The traditional method uses the Z-test, which compares a subject against a set of euploid controls, where the information of fetal fraction is not fully utilized. Here we present a Bayesian method that leverages informative priors on the fetal fraction. METHOD: Our Bayesian method combines the Z-test likelihood and informative priors of the fetal fraction, which are learned from the sex chromosomes, to compute Bayes factors. Bayesian framework can account for nongenetic risk factors through the prior odds, and our method can report individual positive/negative predictive values. RESULTS: Our Bayesian method has more power than the Z-test method. We analyzed 3,405 NIPS samples and spotted at least 9 (of 51) possible Z-test false positives. CONCLUSION: Bayesian NIPS is more powerful than the Z-test method, is able to account for nongenetic risk factors through prior odds, and can report individual positive/negative predictive values.
PURPOSE: Noninvasive prenatal screening (NIPS) sequences a mixture of the maternal and fetal cell-free DNA. Fetal trisomy can be detected by examining chromosomal dosages estimated from sequencing reads. The traditional method uses the Z-test, which compares a subject against a set of euploid controls, where the information of fetal fraction is not fully utilized. Here we present a Bayesian method that leverages informative priors on the fetal fraction. METHOD: Our Bayesian method combines the Z-test likelihood and informative priors of the fetal fraction, which are learned from the sex chromosomes, to compute Bayes factors. Bayesian framework can account for nongenetic risk factors through the prior odds, and our method can report individual positive/negative predictive values. RESULTS: Our Bayesian method has more power than the Z-test method. We analyzed 3,405 NIPS samples and spotted at least 9 (of 51) possible Z-test false positives. CONCLUSION: Bayesian NIPS is more powerful than the Z-test method, is able to account for nongenetic risk factors through prior odds, and can report individual positive/negative predictive values.