proteiNorm – A User-Friendly Tool for Normalization and Analysis of TMT and Label-Free Protein Quantification

The
technological advances in mass spectrometry allow us to collect
more comprehensive data with higher quality and increasing speed.
With the rapidly increasing amount of data generated, the need for
streamlining analyses becomes more apparent. Proteomics data is known
to be often affected by systemic bias from unknown sources, and failing
to adequately normalize the data can lead to erroneous conclusions.
To allow researchers to easily evaluate and compare different normalization
methods via a user-friendly interface, we have developed “proteiNorm”.
The current implementation of proteiNorm accommodates preliminary
filters on peptide and sample levels followed by an evaluation of
several popular normalization methods and visualization of the missing
value. The user then selects an adequate normalization method and
one of the several imputation methods used for the subsequent comparison
of different differential expression methods and estimation of statistical
power. The application of proteiNorm and interpretation of its results
are demonstrated on two tandem mass tag multiplex (TMT6plex and TMT10plex)
and one label-free spike-in mass spectrometry example data set. The
three data sets reveal how the normalization methods perform differently
on different experimental designs and the need for evaluation of normalization
methods for each mass spectrometry experiment. With proteiNorm, we
provide a user-friendly tool to identify an adequate normalization
method and to select an appropriate method for differential expression
analysis.