How to use R packages to identify differentially expressed genes for a Coursework

How to use R packages to identify differentially expressed genes for a real data set - Coursework Example The data were classified according to the gene expressions before and after application of the drug on patients. However, owing to time constraints, some important operations that would have allowed the analysis to exhibit more of its features were left out. For example the arrays were given a summative test at every level; that is t-tests, ebayes and samr. The arrays would have exhibited more underlying relations if the individual cases were matched against their resultant gene expressions after the administration of the drug. The columns could alternatively have been split up in pairs to come up with several individual files that would allow the execution of singular tests on individual files, thereby making the results even more focused. The only weakness of this approach is the need to further recombine the individual results from the tests, but which can not be addressed by the use of the combined arrays. With more time the tests would also have been described under varying p-values. By varying the p-value, it is possible to know the levels of accuracy that similar tests should be subjected to in future. This sets a crucial precedent especially since same method of study will be repeated for future