Probabilistic SNP genotyping at low DNA concentrations

We present a statistical method for biallelic SNP genotyping that reduces the risk of wrong SNP calls and gives fewer no-calls. The method uses a symmetric multinomial logistic regression model with an intuitive graphical interpretation. Its probabilistic nature gives the user control over the accepted risk through the estimated genotype probabilities. We compared the performance of our method with the HID SNP Genotyper v.4.3.1 plug-in (HSG) (Thermo Fisher Scientific) and the additional criteria of the University of Copenhagen (UCPH) through a series of six DNA dilutions from 500 pg to 16 pg DNA. The HSG method made wrong calls from 62.5 pg DNA and below, while the UCPH method made wrong calls at 16 pg DNA. Our method allowed SNP genotyping of 16 pg DNA without making wrong calls. Depending on the DNA dilution, our method also reduced the number of no-calls by 70–96 % compared to UCPH method and 59–69 % compared to the HSG method. Our method can be used for any biallelic genotyping.