Section: New Results

Sequence comparison

Amplicon alignment

Participants: S. Brillet, C. Deltel, P. Durand, D. Lavenier, I. Petrov

Many metagenomics projects identify species by the studying16S-RNA sequences. This is mainly done by comparing the amplicons with 16S-RNA bacterial banks (amplicons are short fragments sequenced from very specific genome areas). As these sequences share a lot of similarities, immediate blast-like heuristics achieve poor performances. To speed up the process, we first select informative k-mers, from both the amplicon dataset and in the RNA16 bank (informative k-mers are defined as under represented k-mers). An index is built from this reduced set of k-mers and a "seed-and-extend" procedure is run. This strategy avoids many non-useful computation and accelerate the overall computation by two orders of magnitude. This new approach is currently implemented in the PLAST software (Regional KoriPlast2 project).

Metagenomics datasets comparison

Participants: G. Benoit, D. Lavenier, C. Lemaitre, P. Peterlongo, G. Rizk

We developp a new method, called Simka, to compare simultaneously numerous large metagenomics datasets. The method computes pairwise distances based on the amount of shared k-mers between datasets. The method scales to a large number of datasets thanks to an efficient kmer-counting step that processes all datasets simultaneoulsy. Additionnally, several distance definitions were implemented and compared, including some originating from the ecological domain. The method is currently applied to the TARA oceans project (more than 500 datasets) which aims at comparing worldwide sea water samples (ANR HydrGen project) [39] .