Multiple testing in large-scale contingency tables: inferring patterns of pair-wise amino acid association in beta-sheets.
This study examines the feasibility of using multiple testing procedures for an inference of independence of categories in each cell in contingency tables. In the simulation study, we compare the performance of various multiple testing procedures in a contingency table setup and demonstrate the relationship among the proportion of true null hypothesis, type I error, power, and false discovery rate. Finally, we apply the proposed methodology to identify the patterns of pair-wise associations of amino acids involved in beta-sheet bridges in proteins. We identify a number of amino acid pairs that exhibit either strong or weak association.
Department of Industrial and Manufacturing Systems Engineering, University of Texas at Arlington, TX 76019, USA. sbkim@uta.edu
Seoung Bum
SB
Kim
Kwok-Leung
KL
Tsui
Mark
M
Borodovsky
D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005189:False Positive Reactions; D015233:Models, Statistical; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012107:Research Design
D000596:Amino Acids; D011506:Proteins