A new analysis tool for individual-level allele frequency for genomic studies

Area of Science:

• Population Genetics
• Genomics
• Bioinformatics

Background:

• Allele frequency is a critical population index for genetic studies.
• Genotype-based estimation can lead to data loss and genotyping errors.

Purpose of the Study:

• To develop a unified intensity-measuring approach for accurate individual-level allele frequency estimation.
• To establish comprehensive databases of coefficients of preferential amplification/hybridization (CPA) and allele frequencies.
• To create and apply novel analytical methods for various genomic applications using accurate allele frequency data.

Main Methods:

• Utilized a unified intensity-measuring approach for allele frequency estimation in 1,104 and 1,270 samples.
• Employed Affymetrix Human Mapping 100K and 500K SNP arrays.
• Adjusted allele frequencies using coefficients of preferential amplification/hybridization (CPA).
• Developed and packaged analytical methods into the ALOHA software.

Main Results:

• The CPA adjustment significantly improved allele frequency estimation accuracy.
• CPA accuracy was robust across different data acquisition times, lab sites, gene chips, and phenotypic statuses.
• Successfully applied accurate allele frequency estimates to discover genomic patterns, detect abnormalities, classify samples, identify outliers, and estimate tumor purity.

Conclusions:

• This study presents the first simultaneous application of individual-level allele frequency analysis for multiple genetic/genomic applications.
• The developed databases and ALOHA software provide valuable resources for human genome analysis using SNP arrays.
• ALOHA software is available for download, facilitating broader research applications.