Sensitive quantification of mosaicism using high density SNP arrays and the cumulative distribution function

Area of Science:

• Genomics
• Medical Genetics
• Bioinformatics

Background:

• Exome and genome sequencing are increasingly used in medicine for disease diagnosis and management.
• Somatic mosaicism, where cells have different genetic makeups, contributes significantly to undiagnosed human diseases.
• Current sequencing methods often fail to detect somatic mosaicism effectively.

Purpose of the Study:

• To present a novel, rapid, and sensitive method for quantifying somatic mosaicism.
• To apply this method to single nucleotide polymorphism (SNP) array data for genome-wide analysis.
• To demonstrate the method's utility in identifying novel diseases and underlying mechanisms.

Main Methods:

• Development and application of the Continuous Distribution Function (CDF) method.
• Utilizing single nucleotide polymorphism (SNP) array data for analysis.
• Quantification of somatic mosaicism across the genome.

Main Results:

• The CDF method provides a rapid and sensitive means to quantify somatic mosaicism.
• Successful application of the method to identify novel genetic diseases.
• Demonstration of new disease mechanisms linked to somatic mosaicism.

Conclusions:

• The developed method significantly enhances the detection of somatic mosaicism.
• This advancement aids in diagnosing previously undiagnosed diseases.
• The approach offers new insights into disease mechanisms driven by somatic mosaicism.