Lipids@Wayne: Bioinformatics Tools for Data-Driven Analysis of Metabolomics and Lipidomics Data

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Date: December 15, 2021
Time: 4:00 p.m. - 5:00 p.m.
Location: Zoom
Category: Seminar

All are welcome to attend our biweekly Lipids@Wayne seminar.

Speaker: Dr. Alla Karnovsky, Associate Professor of Computational Medicine and Bioinformatics, the University of Michigan, Ann Arbor

Title: Bioinformatics Tools for Data-Driven Analysis of Metabolomics and Lipidomics Data

Location: Zoom
https://wayne-edu.zoom.us/j/95547677931?pwd=WUIvKzRwNHJXbXg5QnNtQy9hWXdSZz09

Date and Time: 4 pm on Wednesday, December 15, 2021

Abstract: Metabolomics and lipidomics generate increasingly large and complex datasets that require powerful statistical and bioinformatics tools. A well-established approach to linking alterations in metabolite levels to specific biological processes is to map experimentally measured metabolites to known biochemical pathways and to identify the pathways that are significantly enriched with those. However, traditional enrichment analysis techniques have limited utility for the analysis of lipidomics and untargeted metabolomics data.  

We developed an alternative approach, which relies on extracting meaningful associations between metabolites/lipids directly from the experimental data.  I will describe our Differential Network Enrichment Analysis method that is implemented in our new user-friendly tool Filigree (http://metscape.med.umich.edu/filigree.html). It uses joint structural sparsity estimation to build partial correlation networks from the data, performs consensus clustering to identify highly connected subnetworks, and tests them for enrichment using Network-based Gene Set Analysis (NetGSA).  I will discuss several applications of Filigree for the analysis of metabolomics and lipidomics data from type I and type II diabetes, and chronic kidney disease. 

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