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Activity Number: 299 - SPEED: Recent Advances in Statistical Genomics and Genetics
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract #329661 Presentation
Title: Differential Abundance Analysis with Empirical Bayes Shrinkage Estimation of Variance (DASEV) for Proteomic and Metabolomic Data
Author(s): Zhengyan Huang* and Chi Wang and Arnold Stromberg
Companies: and University of Kentucky and University of Kentucky
Keywords: Mass spectrometry; Zero inflated; Point mass values; Proteomics; Metabolomics

Mass spectrometry (MS) is widely used for proteomic and metabolomic profiling of biological samples. Data obtained by MS are often zero-inflated. Those zero values are called point mass values (PMVs). Zero values can be further grouped into biological PMVs and technical PMVs. The former type is caused by the absence of compounds and the later type is caused by detection limit. A left-inflated mixture likelihood ratio test (LIM) was developed to separate the two types of zeros apart and to perform the differential abundant analysis comparing samples from different treatment groups. However, we notice that LIM may underestimate the variance and thus lead to false positive result when the number of non-zero values is small. We propose a new differential abundance analysis method, DASEV, which uses an empirical Bayes shrinkage method to more robustly estimate the variance and enhance the accuracy of differential abundance analysis. Simulation studies and real data analysis show the improvement of our proposed method compared to LIM.

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

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