encode commit

_freeze/notebooks/ENCODE_project/execute-results/html.json

@@ -0,0 +1,15 @@
+{
+  "hash": "ceedd343dc07b96c4af9c4a939f8d621",
+  "result": {
+    "engine": "knitr",
+    "markdown": "---\ntitle: \"Analyzing Cloud Data from ENCODE\"\nsubtitle: \"The Encyclopedia of DNA Element (ENCODE)\"\nformat: html\neditor: visual\n---\n\n\n# Introduction\n\nThe Encyclopedia of DNA Elements ([ENCODE](https://www.encodeproject.org/)) is a collection of experimental results (from human, mouse, worm and fly) and computing resources devoted to elaborating the mechanisms of gene regulation. \n\nWe will use Bioconductor to acquire and interpret ENCODE resources. In particular, we'll analyze ChIP-Seq, ATAC-Seq and CRISPR interference RNA-Seq experiments.\n\n# ENCODE ChIP-seq Data\n\n\n\n\n::: {.cell}\n\n:::\n",
+    "supporting": [],
+    "filters": [
+      "rmarkdown/pagebreak.lua"
+    ],
+    "includes": {},
+    "engineDependencies": {},
+    "preserve": {},
+    "postProcess": true
+  }
+}

notebooks/ENCODE_project.qmd

@@ -0,0 +1,18 @@
+---
+title: "Analyzing Cloud Data from ENCODE"
+subtitle: "The Encyclopedia of DNA Element (ENCODE)"
+format: html
+editor: visual
+---
+
+# Introduction
+
+The Encyclopedia of DNA Elements ([ENCODE](https://www.encodeproject.org/)) is a collection of experimental results (from human, mouse, worm and fly) and computing resources devoted to elaborating the mechanisms of gene regulation.
+
+We will use Bioconductor to acquire and interpret ENCODE resources. In particular, we'll analyze ChIP-Seq, ATAC-Seq and CRISPR interference RNA-Seq experiments.
+
+# ENCODE ChIP-seq Data
+
+```{r}
+
+```

notebooks/TCGA.qmd

@@ -1,6 +1,6 @@
 ---
 title: "Integrative Analysis with TCGA Data"
-subtitle: "Analysis of Mutation Data from The Cancer Genome Atlas (TCGA)"
+subtitle: "Analysis of Mutation, Transcription and Methylation Data from The Cancer Genome Atlas (TCGA)"
 format: html
 editor: visual
 ---
@@ -247,8 +247,7 @@ ggsave(paste0(path,"samples_with_mut.jpeg"), device = "jpeg")
 
 ```
 
-![Samples with specific mutation per gene](images/samples_with_mut.jpeg)
-## Linking mutations and tumor stage
+![Samples with specific mutation per gene](images/samples_with_mut.jpeg) \## Linking mutations and tumor stage
 
 Now that we are familiarized with the mutation data, we can link mutations to the tumor stage from the patients with rectum adenocarcinoma.
 
@@ -327,6 +326,7 @@ rnaseq = readData[[2]]
 rnaseq
 
 ```
+
 As before, we need to shorten the sample IDs so they can match to the clinical data.
 
 ```{r}
@@ -348,7 +348,7 @@ rnaseq <- rnaseq[,!idx]
 
 ```
 
-Then, we can use the `limma` package to proceed with the differential expression analysis. In this case, we'll ise the tumor stage as a variable to explain the expression of the genes. 
+Then, we can use the `limma` package to proceed with the differential expression analysis. In this case, we'll ise the tumor stage as a variable to explain the expression of the genes.
 
 ```{r}
 
@@ -462,4 +462,3 @@ me_rna_cor = function(sym, mpick = 3){
 me_rna_cor("TAC1", mpick=3)
 
 ```
-