Mining Lipidomics for Biological Insight

Event status:

You are welcome to attend the following joint La Trobe statistics and stochastic seminar.

Date:
Thursday 07 April 2022 12:00 pm until Thursday 07 April 2022 01:00 pm (Add to calendar)
Contact:
Andriy Olenko
a.olenko@latrobe.edu.au
Presented by:
Nicholas Sing
Type of Event:
Seminar/Workshop/Training

Abstract:

Lipidomics is the study of all lipids that make up cells and organisms. Abnormal lipid metabolism is associated with many cardiovascular risk factors. The Baker Heart and Diabetes Institute has generated lipidomic datasets for several population studies. During lipidomic analysis unwanted variation can arise due to variation in laboratory processing and handling, which unwanted variation removal algorithms aim to minimise. This project aims to develop multivariate methodologies for dealing with unwanted variation in lipidomic datasets and modelling the metabolic associations between groups of lipid species and participant characteristics. In this project we are using lipid set enrichment analysis and eigenlipids to explore lipid biology associated with cardiovascular disease. To identify technical sources of unwanted variation in the plasma lipidome during laboratory processing we performed a laboratory experiment and utilised the Remove Unwanted Variation-III (RUV-III) algorithm to remove these sources of unwanted variation from the lipidomic dataset we acquired. We intend to use this as a basis to identify negative control lipids to remove similar sources of unwanted variation in population lipidomic datasets using RUV-III.

Type of Event: Seminar/Workshop/Training

Zoom meeting link:

Join from a PC, Mac, iOS or Android: https://latrobe.zoom.us/j/89942219319

Or iPhone one-tap (Australia Toll): +61280152088,89942219319#

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Dial: +61 2 8015 2088

Meeting ID: 899 4221 9319

International numbers available: https://latrobe.zoom.us/u/kevhrr7gNM

Or a H.323/SIP room system:

Dial: 89942219319@zoom.aarnet.edu.au

or 89942219319@zmau.us

or 103.122.166.55

Meeting ID: 89942219319

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SIP:89942219319@lync.zoom.

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