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Activity Number: 581 - Advanced Cross-Disciplinary Statistical Methods in Statistical Genomics
Type: Topic Contributed
Date/Time: Thursday, August 6, 2020 : 3:00 PM to 4:50 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #311153
Title: Multiomics Analysis of the Immunome, Transcriptome, Microbiome, Proteome, and Metabolome in Pregnancy
Author(s): Nima Aghaeepour*
Companies: Stanford University - Stanford, CA
Keywords: Multiomics; Pregnancy; Machine Learning

Recent technological advances in science provide novel opportunities to unravel the complex biology of pregnancy. Immunological changes during pregnancy are highly dynamic and involve multiple interconnected biological systems. An ongoing cohort study by the March of Dimes Prematurity Research Center at Stanford University exploits recent technological advances to examine of the transcriptomic, microbiome, and proteomic events associated with normal and pathological pregnancies. We will discuss a machine learning algorithm that will integrate mass cytometry data into this multiomics setting. This computational pipeline can increase predictive power and reveal new biology, by combining datasets of various sizes and modularities in a balanced manner. We will next demonstrate how this model can be used to study preterm birth, the leading cause of death in children under 5 years old.

Authors who are presenting talks have a * after their name.

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