TCPA_correlation.Rmd

---
title: "TCPA analysis"
output:
  html_document:
    toc: true
    # toc_float: true
    theme: united
    # theme: cerulean
    # number_sections: true
date: "`r Sys.Date()`"
author: "Mikhail Dozmorov"
---

```{r setup, echo=FALSE, message=FALSE, warning=FALSE}
# Set up the environment
library(knitr)
opts_chunk$set(cache.path='cache/', fig.path='img/', cache=F, tidy=T, fig.keep='high', echo=F, dpi=100, warnings=F, message=F, comment=NA, warning=F, results='as.is', fig.width = 10, fig.height = 6) #out.width=700, 
library(pander)
panderOptions('table.split.table', Inf)
set.seed(1)
library(dplyr)
options(stringsAsFactors = FALSE)
```

```{r settings}

selected_protein <- "MCL1"
```


# Data summary

Data from http://tcpaportal.org/tcpa/download.html. Download pan-cancer data `TCGA-PANCAN19-L4`.

```{r}
annot <- readr::read_delim("/Users/mdozmorov/Documents/Data/GenomeRunner/TCGAsurvival/TCGA-PANCAN19-L4/TCGA-PANCAN19-L4-META.tsv", delim = "\t")
DT::datatable(annot[ !is.na(annot$`TCGA-PANCAN19-L4`), ])
```

# Available proteins

Search (case-insensitive) for a protein of interest, e.g., `r selected_protein`

```{r}
proteins <- readLines("TCPA_proteins.txt")
# knitr::wrap_rmd(text = sort(proteins))
# proteins[ grep(selected_protein, proteins, ignore.case = TRUE) ]
DT::datatable(data.frame(Protein = sort(proteins)))
```

# Protein expression data

First three columns of the data: "Sample_ID" (e.g., TCGA-FI-A2EY-01A-21-A23Z-20), "Cancer_Type" (e.g., COAD), "Sample_Type" (Metastatic - 178 samples, Primary - 4,979 samples), "SetID" (eight numerical IDs). Upper-left corner of the matrix is shown.

```{r}
mtx <- readr::read_csv("/Users/mdozmorov/Documents/Data/GenomeRunner/TCGAsurvival/TCGA-PANCAN19-L4/TCGA-PANCAN19-L4.csv.gz")
DT::datatable(mtx[1:10, 1:10])
```