Statistical challenges in the analysis of two-dimensional difference gel electrophoresis experiments using DeCyder™
Statistical challenges in the analysis of two-dimensional difference gel electrophoresis experiments using DeCyder™
复制标题
DOI：
10.1093/bioinformatics/bti612
复制
发表时间：
2005-10-01
期刊：
影响因子：
5.8
通讯作者：
McCutchen-Maloney, SL
中科院分区：
文献类型：
--
作者：
Fodor, IK;Nelson, DO;McCutchen-Maloney, SL
动机：DeCyder软件(GE Healthcare)是目前用于分析二维差示凝胶电泳(2D DGE)实验的最先进的商业产品。通过结合微阵列数据分析文献的最新进展，建议对DeCyder进行补充分析。结果：对归一化的2D DGE数据进行了更严格的统计检验，减少了从DeCyder获得的潜在差异表达蛋白质的数量，并增加了在人类临床研究中检测差异表达的置信度。
Motivation: The DeCyder software (GE Healthcare) is the current state-of-the-art commercial product for the analysis of two-dimensional difference gel electrophoresis (2D DIGE) experiments. Analyses complementing DeCyder are suggested by incorporating recent advances from the microarray data analysis literature. A case study on the effect of smallpox vaccination is used to compare the results obtained from DeCyder with the results obtained by applying moderated t-tests adjusted for multiple comparisons to DeCyder output data that was additionally normalized.Results: Application of the more stringent statistical tests applied to the normalized 2D DIGE data decreased the number of potentially differentially expressed proteins from the number obtained from DeCyder and increased the confidence in detecting differential expression in human clinical studies.