Update README.md

README.md

@@ -1,3 +1,31 @@
 # Differential Gene-Expression Analysis with Machine Learning Using Dexamethasone Treatment Data
 
-Worked with fellow peers at University of Pittsburgh under supervision of Dr. Junshu Bao, Department of Statistics, University of Pittsburgh, to do a Differential Gene Expression Analysis on a Dexamethasone treatment data set and incorporated Machine Learning into project. 
+**Introduction** 
+
+Worked with [Nityam Rathi](https://www.linkedin.com/in/nityam-rathi-75ab38128/), [Matt Eckelmeyer](https://www.linkedin.com/in/matthew-eckelmeyer-829b8b158/) and Kevin Coleman at University of Pittsburgh under supervision of [Dr. Junshu Bao](https://www.stat.pitt.edu/people/junshu-bao), Department of Statistics, University of Pittsburgh. 
+
+The purpose of this project was to do a Differential Gene Expression Analysis on a Dexamethasone Treatment data set and incorporate Machine Learning to predict which genes could be differentially expressed. 
+
+The datasets used are found under the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) accession number [GSE6711](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE6711). We specifically used files `GSM154262.txt, GSM154263.txt, GSM154264.txt, GSM154277.txt, GSM154278.txt, GSM154279.txt`. 
+
+Dexamethasone specifically affects cell growth and can cause apoptosis (cell death) as specified [here](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5620202/). 
+
+**Files** 
+
+📜 `Source Code.Rmd`
+
+Contains the R Markdown code needed to create the final PDF file. 
+
+📜 `Dexamethasone Treatment Differential Gene Expression Analysis with Machine Learning.pdf`
+
+Final PDF file outputted from knitting the source code. Contains all goals, steps, explanations of procedure for this research. 
+
+**Contact Information** 
+
+![interests](https://avatars1.githubusercontent.com/u/38919947?s=400&u=49ab1365a14fac78a91e425efd583f7a2bcb3e25&v=4)
+
+Yogindra Raghav (YogiOnBioinformatics) 
+
+[email protected]
+
+