A Bootstrap based Nonparametric Analysis of Variance (NANOVA) on RNA-seq data of yeast Glaciozyma Antarctica PI12

摘要

The development of statistical methods for big data such as RNA-seq is an active genomics research nowadays. In this study, full factorial design is used to perform the Analysis of Variance (ANOVA). Since normality assumption did not hold for these datasets, a bootstrap based nonparametric Analysis of Variance (NANOVA) was chosen as alternative to ANOVA test. This study provides the full factorial design approach on NANOVA test The result shows that the NANOVA methods gives high area under the curve (AUC) value that indicate the methods is suitable for this type of dataset.