The original data for <b>Strategies of </b><b>improved </b><b>data preprocess</b><b>ing</b><b> enhance the power of noninvasive prenatal </b><b>screening in detecting microdeletion</b><b>syndromes</b>

Noninvasive prenatal screening (NIPS) has become widely adopted for assessment of common trisomies, but technical variability hinders reliable identification of rarer microdeletion syndromes. Here, we implement advanced mappability correction and principal component analysis prior to NIPS, which minimizes noise and batch effects in the data. Consequently, our approach, termed IDP, achieves substantially higher sensitivity and specificity for five examined microdeletions versus standard preprocessing controls. Using 2,865 clinical samples and 100 simulated datasets, we comprehensively validate IDP's capabilities. We also propose two new quality metrics, abnormal rate and disperse index, to monitor fluctuations throughout processing. Together, this study provides a robust framework to expand NIPS utility for a broader range of prenatal genetic conditions.