KinSNP software for homozygosity mapping of disease genes using SNP microarrays

We present KinSNP, a user-friendly software tool for homozygosity mapping using SNP arrays. The software searches for stretches of SNPs which are homozygous to the same allele in all ascertained sick individuals. User-specified parameters control the number of allowed genotyping 'errors' within homozygous blocks. Candidate disease regions are then reported in a detailed, coloured Excel file, along with genotypes of family members and healthy controls. An interactive genome browser has been included which shows homozygous blocks, individual genotypes, genes and further annotations along the chromosomes, with zooming and scrolling capabilities. The software has been used to identify the location of a mutated gene causing insensitivity to pain in a large Bedouin family. KinSNP is freely available from http://bioinfo.bgu.ac.il/bsu/software/kinSNP webcite.The availability of high-density mapping microarrays, bearing sufficient probes to analyse 10,000-1,000,000 single nucleotide polymorphisms (SNPs) in one assay, offers an efficient alternative to traditional, microsatellite-based, genome-wide linkage scans [1]. Accordingly, several public linkage software programs have been developed, such as Allegro, EasyLinkage and dChip, which can handle the high number of SNPs in these arrays. All of these have been successfully used for mapping Mendelian disorders [2-4].Genotyping individuals from large, multiply-consanguineous families of isolated populations offers a unique advantage for positional cloning of rare diseases [5,6]. A mutation occurring in a founder may be rapidly inherited by numerous individuals in the population, and the offspring of consanguineous parents will have a high probability of inheriting two copies of the mutated chromosomal segment and thus expressing the disease. Classical linkage analysis of SNP arrays in these studies is highly problematic, however, due to the computational load needed to deal with both the large number of SNPs and the family struc