Processing of data generated by 2-dimensional gel electrophoresis for statistical analysis: missing data, normalization, and statistics.
Several high-throughput statistical methods were evaluated for processing data generated by two-dimensional polyacrylamide gel electrophoresis, including how to handle missing data, normalization, and statistical analysis of data obtained from 2-D gels. Quantile normalization combined with a nonparametric permutation test based on minimizing false discover rates gave the highest yield of proteins that changed with genotype and detected the anticipated 50% decrease in Mn-superoxide dismutase (MnSOD) protein levels in mitochondrial extracts obtained from MnSOD-deficient mice.
Chang
Jinsook
J
Department of Cellular and Structural Biology, University of Texas Health Science Center at San Antonio, San Antonio, TX 78284-7762, USA.
Van Remmen
Holly
H
Ward
Walter F
WF
Regnier
Fred E
FE
Richardson
Arlan
A
Cornell
John
J
D000818:Animals; D001330:Electronic Data Processing / Q000379:methods*; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods* / Q000706:statistics & numerical data; D005838:Genotype; D051379:Mice; D008928:Mitochondria / Q000737:chemistry; D011506:Proteins / Q000032:analysis / Q000235:genetics; D040901:Proteomics / Q000379:methods*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D013223:Statistics as Topic / Q000379:methods; D013482:Superoxide Dismutase / Q000032:analysis / Q000172:deficiency
D011506:Proteins; D013482:Superoxide Dismutase