TY - JOUR
T1 - PHOENIX, a web interface for (re)analysis of microarray data.
AU - Berger, Fabrice
AU - De Hertogh, Benoit
AU - Bareke, Eric
AU - Pierre, Michael
AU - Gaigneaux, Anthoula
AU - Depiereux, Eric
PY - 2009
Y1 - 2009
N2 - Microarrays are tools to study the expression profile of an entire genome. Technology, statistical tools and biological knowledge in general have evolved over the past ten years and it is now possible to improve analysis of previous datasets. We have developed a web interface called PHOENIX that automates the analysis of microarray data from preprocessing to the evaluation of significance through manual or automated parameterization. At each analytical step, several methods are possible for (re)analysis of data. PHOENIX evaluates a consensus score from several methods and thus determines the performance level of the best methods (even if the best performing method is not known). With an estimate of the true gene list, PHOENIX can evaluate the performance of methods or compare the results with other experiments. Each method used for differential expression analysis and performance evaluation has been implemented in the PEGASE back-end package, along with additional tools to further improve PHOENIX. Future developments will involve the addition of steps (CDF selection, geneset analysis, meta-analysis), methods (PLIER, ANOVA, Limma), benchmarks (spike-in and simulated datasets), and illustration of the results (automatically generated report).
AB - Microarrays are tools to study the expression profile of an entire genome. Technology, statistical tools and biological knowledge in general have evolved over the past ten years and it is now possible to improve analysis of previous datasets. We have developed a web interface called PHOENIX that automates the analysis of microarray data from preprocessing to the evaluation of significance through manual or automated parameterization. At each analytical step, several methods are possible for (re)analysis of data. PHOENIX evaluates a consensus score from several methods and thus determines the performance level of the best methods (even if the best performing method is not known). With an estimate of the true gene list, PHOENIX can evaluate the performance of methods or compare the results with other experiments. Each method used for differential expression analysis and performance evaluation has been implemented in the PEGASE back-end package, along with additional tools to further improve PHOENIX. Future developments will involve the addition of steps (CDF selection, geneset analysis, meta-analysis), methods (PLIER, ANOVA, Limma), benchmarks (spike-in and simulated datasets), and illustration of the results (automatically generated report).
KW - Affymetrix - Benchmark - Consensus - Differential expression - Microarray - Regularized t-test - SAM - Statistical analysis - Web interface - Window t-test
M3 - Article
VL - 4
SP - 603
EP - 618
JO - Central European Journal of Biology
JF - Central European Journal of Biology
IS - 4
ER -