Mapping genomic variants is an important and necessary step for biomedical and fundamental research. Differences in our genomic sequences result in phenotypic differences that determine how, for example, the cells of a healthy and a diseased person differ from each other. In population genetics, genomic variants help to trace down our evolutionary histories.
Genomic differences are now routinely measured using high-throughput sequencing techniques. However, using standard techniques, we only know whether there is a variant at a given position, but not on which of the two copies of the chromosome it resides. In medical genomics, discovering combinations of genetic variants on the same chromosomal copy can bring forward clinically relevant phenotypes. In population genetics, the reconstruction of these chromosome sequences, called haplotypes, are a prerequisite for fine-grained analyses of the history of mankind.
DFG now funds a cooperation project between the Algorithmic Bioinformatics group at HHU and the Max Planck Institute for Informatics in Saarbrücken that will develop algorithms for genomics at haplotype-level, that is, at full resolution of the two chromosomal copies. This implies solving challenging problems involving the assignment of millions of reads to the chromosomal copy they came from. The results of this project will be made directly available via the open source WhatsHap software suite.