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

Abstract

BackgroundAllele frequency is one of the most important population indices and has been broadly applied to genetic/genomic studies. Estimation of allele frequency using genotypes is convenient but may lose data information and be sensitive to genotyping errors.ResultsThis study utilizes a unified intensity-measuring approach to estimating individual-level allele frequencies for 1,104 and 1,270 samples genotyped with the single-nucleotide-polymorphism arrays of the Affymetrix Human Mapping 100K and 500K Sets, respectively. Allele frequencies of all samples are estimated and adjusted by coefficients of preferential amplification/hybridization (CPA), and large ethnicity-specific and cross-ethnicity databases of CPA and allele frequency are established. The results show that using the CPA significantly improves the accuracy of allele frequency estimates; moreover, this paramount factor is insensitive to the time of data acquisition, effect of laboratory site, type of gene chip, and phenotypic status. Based on accurate allele frequency estimates, analytic methods based on individual-level allele frequencies are developed and successfully applied to discover genomic patterns of allele frequencies, detect chromosomal abnormalities, classify sample groups, identify outlier samples, and estimate the purity of tumor samples. The methods are packaged into a new analysis tool, ALOHA (Allele-frequency/Loss-of-heterozygosity/Allele-imbalance).ConclusionsThis is the first time that these important genetic/genomic applications have been simultaneously conducted by the analyses of individual-level allele frequencies estimated by a unified intensity-measuring approach. We expect that additional practical applications for allele frequency analysis will be found. The developed databases and tools provide useful resources for human genome analysis via high-throughput single-nucleotide-polymorphism arrays. The ALOHA software was written in R and R GUI and can be downloaded at http://www.stat.sinica.edu.tw/hsinchou/genetics/aloha/ALOHA.htm.

LOHAS: loss‐of‐heterozygosity analysis suite

“…The combined LOH/LCSH plots facilitate the identification of regions of LOH/LCSH characterized by an individual-specific LOH/LCSH excess; that is a region satisfying that an individual LOH/LCSH curve is higher than a g%-quantile LOH/LCSH reference curve. Third, an LOH/LCSH biplot is developed and enhanced by adapting the conventional biplot [Chapman et al, 2001;Gabriel, 1971;Huggins et al, 2008;Pittelkow and Wilson, 2003;Yang et al, 2010] to study LOH/LCSH. Homozygous intensities of all n samples at all ' windows on the chromosome of interest are arranged as an ' Â n homozygous intensity matrix.…”

An integrated analysis tool for analyzing hybridization intensities and genotypes using new-generation population-optimized human arrays

“…The HI values of all SNPs in a sample are subtracted from the average HI of non-AI SNPs. The AI SNPs must be excluded from the calculation of the average because their HI values are interfered by chromosomal aberrations [ 6 ] or poor data quality [ 97 ]. After normalization, the HI values of different samples become comparable.…”

“…AFs are of two types: population-level AF and individual-level AF [ 4 , 6 ]. This paper focuses on the individual-level AF; therefore, throughout this paper, we have omitted the word “individual-level” when discussing AF.…”

“…On the basis of the CPA + LIM AF estimates, ALICE incorporates our previous confidence interval approach [ 6 ] to detect AI for a SNP. Let denote the genotype-specific mean and standard deviation of the CPA + LIM AF estimates of the m th autosomal SNP in the normal reference samples, respectively.…”

“…ALICE incorporates the confidence interval approach [ 6 ] to detect the status of LOH and LCSH. Notation ℒ stands for an LOH/LCSH analysis.…”