In Silico Fragment Size Selection for Enhanced Fetal Fraction and Abnormality Origin Discernment Using Pair‐End Sequencing of Maternal Plasma DNA

OBJECTIVES: The aim of this study was to develop and evaluate a new bioinformatics pipeline that improves fetal DNA fraction (FF), determines the origin of chromosomal abnormalities, and better detects sex chromosomal aneuploidies (SCAs) than routine NIPT. METHODS: We used a bioinformatic strategy that filters out longer DNA fragments, thereby significantly improving the FF. By combining the filtered data with the original data, we determined the origin of detected abnormalities. RESULTS: We analyzed samples from 204 pregnancies. Using routing NIPT methods, 36 samples were negative, 37 exhibited low FF, and 131 were detected as positive. Applying the method of this study, all the low FF samples were qualified for analysis. Furthermore, 56 samples initially classified as positive were identified to be false positives, predominantly caused by maternal abnormalities. No false negative results were observed with this method. CONCLUSION: We developed a pipeline for NIPT that significantly improves FF, which helps deduce the origin of abnormalities and detect more karyotypes of SCAs. The strategy has the potential to improve the specificity of NIPT.