Inferring fetal fractions from read heterozygosity empowers the noninvasive prenatal screening

Area of Science:

• Genetics
• Molecular Biology
• Bioinformatics

Background:

• Fetal fraction (FF) is crucial for noninvasive prenatal screening (NIPS) using cell-free DNA (cfDNA).
• Accurate FF estimation is essential for reliable NIPS results.

Purpose of the Study:

• To present a novel method for reliably estimating fetal fraction (FF).
• To utilize FF estimation for improved aneuploidy testing and sample analysis in NIPS.

Main Methods:

• Examining autosome single-nucleotide polymorphisms (SNPs) to estimate FF.
• Defining and utilizing read heterozygosity at covered SNPs as a function of FF.
• Applying inferred FF as a prior for Bayes factors in aneuploidy testing.

Main Results:

• Demonstrated the effectiveness of the FF estimation method.
• Observed improved power for aneuploidy detection compared to the Z-test using inferred FF.
• Successfully identified female-male twins in clinical samples through accurate FF inference.

Conclusions:

• Accurate FF estimation significantly improves NIPS efficacy.
• The method enables a powerful Bayesian approach for NIPS.
• Allows for adaptive sequencing strategies and simplified screening for conditions like XXY syndrome.