Extracting very large data in 10-50 million observations or rows that is time consuming just to pull from internet but then read into Rstudio and transform before running machine learning on the top genes. In this case these observations are copy variants in the allele information of the complementary DNA with thymine made from reverse transcription of messenger RNA or mRNA to get what this study in the document used to find multiple sclerosis risk loci variants that enhanced or silenced (upregulated or down regulated) gene activity. This should be interesting and is part of the work to see if their are some common associations with EBV infection at various states. No libraries used just building the data set of common strands of nucleic DNA in 20 base pair fragments. The study used 2 MS patients, 1 control, and 1 commercial line of MS to compare but used repeat RefSeq analysis in 3 repeats on the control and 5 each on the 2 MS patients and commercial line comparison.

Data gsi

First Steps with R

First steps with R