Section: Research Program

Axis 1: Data Structures

The aim of this axis is to develop efficient data structures for representing the mass of genomic data generated by the sequencing machines. This research is motivated by the fact that the treatments of large genomes, such as mammalian or plant genomes, or multiple genomes coming from a same sample as in metagenomics, require high computing resources, and more specifically very important memory configuration. The last advances in TGS technologies bring also new challenges to represent or search information based on sequencing data with high error rate.

Part of our research focuses on the de-Bruijn graph structure. This well-known data structure, directly built from raw sequencing data, have many properties matching perfectly well with NGS processing requirements. Here, the question we are interested in is how to provide a low memory footprint implementation of the de-Bruijn graph to process very large NGS datasets, including metagenomic ones [3], [4].

A correlated research direction is the indexing of large sets of objects. A typical, but non exclusive, need is to annotate nodes of the de-Bruijn graph, that is potentially billions of items. Again, very low memory footprint indexing structures are mandatory to manage a very large quantity of objects [7].