Computational challenges in microbiome research

Abstract

Millions of bacteria make our bodies their home. They help keep us healthy, and disruptions in the normal microbiota are believed to contribute to a number of diseases. Cost-effective sequencing technologies have made it possible to sequence the genomes of human-associated microbial communities, leading to the birth of a new scientific discipline - metagenomics. Analyzing the resulting data, however, poses significant computational challenges, in part due to the sheer size of the data-sets, and in part due to the fact that most of the existing computational framework has been established for single organisms. In my talk I will outline several analytical challenges posed by metagenomic applications, and will describe recent results from my lab in the development of tools for analyzing metagenomic data. In particular I will discuss insights from our analysis of diarrheal disease in developing countries, as well as the effective use of co-abundance approaches for linking together data from two large metagenomic studies.