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+# Lab 3 for the University of Tulsa's CS-6643 Bioinformatics Course
+# Expression Exploratory Analysis 
+# Professor: Dr. McKinney, Fall 2022
+# Noah L. Schrick - 1492657
+
+## Set Working Directory to file directory - RStudio approach
+setwd(dirname(rstudioapi::getActiveDocumentContext()$path))
+
+#### Part A: Loading Data
+## 1: Loading Gene Expression Data
+load("sense.filtered.cpm.Rdata")
+dim(sense.filtered.cpm) 
+colnames(sense.filtered.cpm)
+
+## 2: Demographic Data
+# Loading
+subject.attrs <- read.csv("Demographic_symptom.csv", stringsAsFactors = FALSE)
+dim(subject.attrs)  # 160 subjects x 40 attributes
+colnames(subject.attrs)  # interested in X (sample ids) and Diag (diagnosis)
+subject.attrs$X
+subject.attrs$Diag
+
+# Matching gene expression samples with their diagnosis
+if (!require("dplyr")) install.packages("dplyr")
+library(dplyr)
+# create a phenotype vector
+# grab X (subject ids) and Diag (Diagnosis) from subject.attrs that 
+#   intersect %in% with the RNA-Seq data
+phenos.df <- subject.attrs %>% 
+  filter(X %in% colnames(sense.filtered.cpm)) %>%
+  dplyr::select(X, Diag)  
+colnames(phenos.df) # $Diag is mdd diagnosis
+# grab Diag column and convert character to factor
+mddPheno <- as.factor(phenos.df$Diag)  # this is our phenotype/class vector 
+
+summary(mddPheno) # MDD -- major depressive disorder, HC -- healthy control
+
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