Abstract
Genome wide association studies (GWAS) attempt to map genotypes to phenotypes in organisms. This is typically performed by genotyping individuals using microarray or by aligning whole genome sequencing reads to a reference genome. Both approaches require knowledge of a reference genome which hinders their application to organisms with no or incomplete reference genomes. This caveat can be removed by using alignment-free association mapping methods based on k-mers from sequencing reads. Here we present an improved implementation of an alignment free association mapping method. The new implementation is faster and includes additional features to make it more flexible than the original implementation. We have tested our implementation on an E. Coli ampicillin resistance dataset and observe improvement in execution time over the original implementation while maintaining accuracy in results. We also demonstrate that the method can be applied to find sex specific sequences.
Highlights
Association mapping is the process of associating phenotypes with genotypes
The high plasticity in bacterial genomes means structural variants and even large genomic segments in various strains are missing in the reference genomes which makes application of reference based methods difficult
These methods do not scale to organisms with large genomes, and as many of them have incomplete reference genomes, there were challenges in association mapping in these organisms
Summary
Association mapping is the process of associating phenotypes with genotypes. In genome wide association studies (GWAS), individuals are typically genotyped using microarrays or by aligning sequencing reads from individuals to a reference genome. Associations to k-mers after correcting for population structure are determined.
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