Purpose: Traditional Z-test methods during noninvasive prenatal screens (NIPS) use the fixed parameter of standard deviation (SD), which ignores the influence of actual sequencing read counts of a sample on the results. The aim of this study is to eliminate the influence of the sequencing depth of individual samples on the results and enhance the power of NIPS.
Methods: In this study, we propose an improved NIPS method, which calculates the SD in the Z-score process adaptively according to the actual read count of the test sample. Our approach obtained the SD linear fitting function along with the read count with a large number of reference samples, in which SD and read count fit well. The effectiveness of our enhanced NIPS method was evaluated on three common trisomy syndromes and five recurrent CNV syndromes with 3219 and 6592 samples based on whole genome sequencing of maternal peripheral blood.
Results: A total of 3,219 pregnant samples have been used for validating the proposed method on detecting fetal trisomy syndromes (T13, T18, and T21), in which eight false negative (FN) samples have been corrected as true positive (TP) and eight false positive (FP) samples have been fixed as true negative (TN) with our proposed adaptive-SD method. Another 6592 samples were used to compare the two methods on detecting five recurrent fetal copy number variation (CNV) syndromes, in which the FP samples have decreased from 99 to 39.
Conclusions: Our adaptive-SD NIPS method shows more power on detecting both trisomy syndromes and five recurrent CNVs in the pregnant samples with diverse read counts. Besides, our proposed method contributes to lower FP and FN samples than the traditional Z-test method in NIPS. Our results show that our enhanced NIPS methods are effective in detecting both abnormal fetal trisomy syndromes and recurrent CNV syndromes in pregnant women.
Keywords: Z-test; adaptive parameter; copy number variation; noninvasive prenatal screen; trisomy syndrome.