Guidelines for Bioinformatics and the Statistical Analysis of Omic Data

This chapter is a resource for those designing omics experiments and those analyzing the data from such experiments. It is organized into two parts, one with a focus on bioinformatics tools and techniques, and the other with a focus on statistical analyses. It is intended to be a high-level instructional chapter for those who are interested in performing their own analyses, not a comprehensive discussion of either area. The first section discusses the bioinformatics tools and algorithms used in genomics and transcriptomics. It describes typical workflows and the tools available for performing an omic experiment and underscores the importance of both the tools being used and a clear understanding of the underlying algorithm. The second section describes general study design principles that should be taken into account before an experiment is begun. It describes some basic principles of statistical analysis and commonly used methods. It is not a comprehensive discussion of statistical theory nor does it describe more complex statistical models. The guidance of a statistician is advised for complex study designs, hypotheses, or statistical models.