Life Sciences Commons^™

Large Scale Microbiome Profiling In The Cloud, Camilo Valdes, Vitalii Stebliankin, Giri Narasimhan

Biomolecular Sciences Institute: Faculty Publications

Motivation

Bacterial metagenomics profiling for metagenomic whole sequencing (mWGS) usually starts by aligning sequencing reads to a collection of reference genomes. Current profiling tools are designed to work against a small representative collection of genomes, and do not scale very well to larger reference genome collections. However, large reference genome collections are capable of providing a more complete and accurate profile of the bacterial population in a metagenomics dataset. In this paper, we discuss a scalable, efficient and affordable approach to this problem, bringing big data solutions within the reach of laboratories with modest resources. Results

We developed FLINT, a …

Matria: A Unified Centrality Algorithm, Trevor Cickovski, Vanessa Aguiar-Pulido, Giri Narasimhan

Biomolecular Sciences Institute: Faculty Publications

Background

Computing centrality is a foundational concept in social networking that involves finding the most “central” or important nodes. In some biological networks defining importance is difficult, which then creates challenges in finding an appropriate centrality algorithm.

Results

We instead generalize the results of any k centrality algorithms through our iterative algorithm MATRIA, producing a single ranked and unified set of central nodes. Through tests on three biological networks, we demonstrate evident and balanced correlations with the results of these k algorithms. We also improve its speed through GPU parallelism.

Conclusions

Our results show iteration to be a powerful technique …