Improved normalization of systematic biases affecting ion current measurements in label-free proteomics data.

ABSTRACT: Normalization is an important step in the analysis of quantitative proteomics data. If this step is ignored, systematic biases can lead to incorrect assumptions about regulation. Most statistical procedures for normalizing proteomics data have been borrowed from genomics where their development has focused on the removal of so-called 'batch effects.' In general, a typical normalization step in proteomics works under the assumption that most peptides/proteins do not change; scaling is then used to give a median log-ratio of 0. The focus of this work was to identify other factors, derived from knowledge of the variables in proteomics, which might be used to improve normalization. Here we have examined the multi-laboratory data sets from Phase I of the NCI's CPTAC program. Surprisingly, the m

SUBMITTER: Rudnick PA 

PROVIDER: S-EPMC4014289 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature