SMS scnews item created by John Ormerod at Mon 31 Mar 2014 1528
Type: Seminar
Distribution: World
Expiry: 12 Apr 2014
Calendar1: 11 Apr 2014 1400-1500
CalLoc1: Carslaw 173
Auth: jormerod@pjormerod4.pc (assumed)

# Statistics Seminar: Yuliya Karpievitch (UTAS) -- Quantitative Analysis of Mass Spectrometry Data

Title
Quantitative Analysis of Mass Spectrometry Data

Abstract
Quantification of liquid chromatography mass spectrometry (LC-MS)
data is complicated by missing values. Some are easier to deal
with than others. For example, values missing completely at random
can be ignored or imputed based on the observed peptide abundances.
Left-censored values that fall bellow the detection limit are
harder to deal with as observed values are not representative of
the missing ones. Here I will present a statistical model that
takes into account the ’missingness’ mechanism and imputes the
values accordingly. I will also discuss a normalisation method that
removes biases of arbitrary complexity.


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