Pangenomics, the study of many different genomes from one species, can provide a more holistic picture of the natural variation and mutations that occur within a species than using one singular reference genome.
Although advances in NGS technologies have reduced the cost and increased the speed of sequencing, the data structures and analysis tools needed to study and graphically represent the relationships between millions of sequenced genomes remain a challenge. While graph-based data formats for pangenomes have become popular and widely adopted, they only represent the genetic variation in a collection of genomes, not their shared evolutionary and mutational histories. They also have large storage requirements that do not scale well.
Now, a new data structure and compression technique has been developed that enables the field of pangenomics to handle unprecedented scales of genetic information.
This work is published in Nature Genetics…
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