In this section
@article{Kammers:2015:10.1016/j.euprot.2015.02.002,
author = {Kammers, K and Cole, RN and Tiengwe, C and Ruczinski, I},
doi = {10.1016/j.euprot.2015.02.002},
journal = {EuPA Open Proteomics},
pages = {11--19},
title = {Detecting significant changes in protein abundance},
url = {http://dx.doi.org/10.1016/j.euprot.2015.02.002},
volume = {7},
year = {2015}
}
TY - JOUR
AB - We review and demonstrate how an empirical Bayes method, shrinking a protein's sample variance towards a pooled estimate, leads to far more powerful and stable inference to detect significant changes in protein abundance compared to ordinary t-tests. Using examples from isobaric mass labelled proteomic experiments we show how to analyze data from multiple experiments simultaneously, and discuss the effects of missing data on the inference. We also present easy to use open source software for normalization of mass spectrometry data and inference based on moderated test statistics.
AU - Kammers,K
AU - Cole,RN
AU - Tiengwe,C
AU - Ruczinski,I
DO - 10.1016/j.euprot.2015.02.002
EP - 19
PY - 2015///
SN - 2212-9685
SP - 11
TI - Detecting significant changes in protein abundance
T2 - EuPA Open Proteomics
UR - http://dx.doi.org/10.1016/j.euprot.2015.02.002
UR - http://hdl.handle.net/10044/1/59374
VL - 7
ER -
Dr. Calvin Tiengwe
Dept. of Life Sciences,
503 Sir Ernst Chain Building,
Imperial College London,
SW7 2AZ, UK
