Leveraging Genomics Software to Improve Proteomics Results

Fodor, I K ; Nelson, D O

Lawrence Livermore National Laboratory

关键词: Data Analysis;    99 General And Miscellaneous//Mathematics, Computing, And Information Science;    59 Basic Biological Sciences;    Proteins;    Electrophoresis;   

DOI  :  10.2172/883739
RP-ID  :  UCRL-TR-215176
RP-ID  :  W-7405-ENG-48
RP-ID  :  883739

美国|英语

来源: UNT Digital Library

【 摘 要 】

Rigorous data analysis techniques are essential in quantifying the differential expression of proteins in biological samples of interest. Statistical methods from the microarray literature were applied to the analysis of two-dimensional difference gel electrophoresis (2-D DIGE) proteomics experiments, in the context of technical variability studies involving human plasma. Protein expression measurements were corrected to account for observed intensity-dependent biases within gels, and normalized to mitigate observed gel to gel variations. The methods improved upon the results achieved using the best currently available 2-D DIGE proteomics software. The spot-wise protein variance was reduced by 10% and the number of apparently differentially expressed proteins was reduced by over 50%.