CANCELLED - SEMINAR by Marie Chion (University of Cambridge)

This is a joined ISBA statistics and AHIDDA group seminar by

Marie CHION
MRC Biostatistics Unit, University of Cambridge, Cambridge, UK

on

"Accounting for multiple imputation in differential
quantitative proteomics"

Abstract :
Quantitative proteomics using liquid chromatography-mass spectrometry can identify and quantify several thousand proteins in a few hours of analysis. Differential quantitative proteomics analysis compares the measured intensity of proteins between different
conditions to determine those whose abundance varies "significantly". A particularity of these large datasets analysed is that they contain missing values between 5 and 15%.

One way of dealing with the problem of missing values is to impute them, i.e., to replace them with a value defined by the user or an algorithm. Thus, multiple imputation allows the imputation process to be iterated several times to obtain several complete data sets.
These are then combined before applying conventional statistical tools. However, standard software for statistical analysis of proteomics data uses the average complete dataset and ignores the uncertainty induced by the random imputation process.

Therefore, we present a rigorous method of multiple imputation using Rubin's rules and a variant of the t-moderated test that accounts for the variability arising from both the original dataset and the multiple imputation process.