Project 9 aims to develop a memory efficient tool for SNP selection from whole genome sequence (WGS) data. Users may provide commercial lists of pre-aproved SNPs, lists of SNPs of general interest, and list of SNPs to exclude.
The algorithm selects SNPs that tag other SNPs most efficient across individuals from several African populations. It is based on haplotype (multi-marker) tagging in addition to simple pairwise LD. By using random access to block gzipped files, the algorithm can efficiently process WGS data.
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Python 3.x