Code review of Xiao (#1)

README.md

@@ -1,7 +1,21 @@
-# WorldsSimplestCodeReview
+# Another, quite deep, fork from VAI -> ttriche -> svad98 -> trichelab
 
 [![Build Status](https://travis-ci.org/VanAndelInstitute/WorldsSimplestCodeReview.png?branch=master)](https://travis-ci.org/VanAndelInstitute/WorldsSimplestCodeReview)  [![codecov](https://codecov.io/gh/VanAndelInstitute/WorldsSimplestCodeReview/branch/master/graph/badge.svg)](https://codecov.io/gh/VanAndelInstitute/WorldsSimplestCodeReview)
 
+## Cloning a repo into Rstudio
+
+1. In RStudio, go to File -> New Project
+
+2. In the New Project wizard, choose Version Control -> Git repository
+
+3. Enter the URL of your fork and the location on your local machine where you'd
+   like the repository saved.
+
+4. Then Create Project.
+
+5. In the top-right panel there should be a 'Git' tab where you can see what's
+   changed, pull and push commits, and see the commit history.
+
 ## How to finish setting up your new package
 
 Now that you've got a working package skeleton, there are a few steps to finish setting up all the integrations:

vignettes/TET2.Rmd

@@ -15,8 +15,10 @@ vignette: >
 knitr::opts_chunk$set(echo = TRUE)
 knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
 library(devtools)
-load_all("./")
+load_all("./") 
+# the load_all("./") is necessary to make the code run (DNAme does not work without it)
 ```
+# Reviewed by Svetlana Djirackor
 
 # Installation
 
@@ -85,6 +87,7 @@ dim(DNAme)
 ### Some contrasts
 
 Is it the case that TET2, IDH1, and IDH2 mutations are exclusive?
+_With the exception of GSM604380/patient 316, TET2 and IDH1/2 mutations are exclusive._
 
 ```{r, heatmap, eval=TRUE}
 
@@ -96,6 +99,23 @@ Heatmap(mutations, col=c("lightgray","darkred"), name="mutant", column_km=4,
 
 ```
 
+### Healthy curiosity
+```{r, The OddBall}
+library(tidyverse)
+# one patient is the odd-ball here
+as_tibble(DNAme$`idh1.idh2:ch1`) -> idh1_idh2
+# since there is ch1 and 2, I compared both and they have the exact same information
+# as_tibble(DNAme$`idh1.idh2:ch2`) -> idh1_idh2_next
+# idh1_idh2 == idh1_idh2_next - returns TRUE
+as_tibble(DNAme$`tet2:ch1`) -> tet
+# as_tibble(DNAme$`tet2:ch2`) -> tet_2
+# tet == tet_2 - returns TRUE
+colnames(tet) <- c("TET")
+colnames(idh1_idh2) <- c("IDH")
+compiled <- cbind(tet, idh1_idh2)
+View(compiled) # scrolled through and identified the patient/sample number that had the mutations in both TET2 and IDH
+```
+
 Do we see genome-wide hypermethylation from TET2 mutations? 
 
 ```{r, TET2_vs_IDH}
@@ -151,3 +171,9 @@ fit3 <- eBayes(lmFit(exprs(DNAme)[, as.integer(rownames(design3))], design3))
 # 10 probes for TET2:purity
 
 ```
+
+I'm unsure of how to interpret the code above:
+- The annotation/description of the designs are unclear. 
+- Why would we run the code this way?
+- What do the probe numbers mean?
+- How can this be translated into assessing genome-wide methylation?