SNP+ to predict dropout rates in SNP arrays

Abstract Genotyping individuals using forensic or non-invasive samples such as hair fecal increases the risk of allelic amplification failure (dropout) due to low quality and quantity DNA. One way decrease genotyping errors is increase number replicates per sample. Here, we have developed software SNP+ estimate dropout probability subsequent required obtain reliable genotype with 95%. Moreover, predicts minor allele frequency compares two competing models assuming equal allele-specific probabilities by Bayes factor. The handles data from one SNP high density arrays (e.g., 100,000 SNPs).