Population Calling: a powerful tool for novel mutation detection in larger sample pools

Current Next-Generation Sequencing platforms can sequence large numbers of individual genomes per year, enabling large-scale population genetics. One of the challenges in such large scale re-sequencing efforts is the simultaneous genotyping of all samples in the population.

Simply merging of genotyping results of individual samples results in incomplete variation matrices where unknown scores can be a consequence of insufficient read coverage or simply of a genotype that has not been called because re-sequence sample and reference are identical. The very recently released GENALICE MAP population caller solves this problem in a very efficient and elegant way.

The aggregate information over all samples is used to improve sensitivity and precision to detect variants in a single sample. In other words, the genotyping quality of an individual sample benefits from the information present in other samples in the population. The option to incrementally add samples to an existing experiment makes this solution very scalable.

In this workshop we show our first experience with the GENALICE MAP population caller on large scale re-sequencing data in plant genomes. A comparison with the classical way of population calling will be provided.