report_main.Rmd

---
title: "Pan-cancer quantification of neoantigen-mediated immunoediting in cancer evolution"
author: ["Tao Wu","Xue-Song Liu (Corresponding author)"]
date: "`r Sys.Date()`"
output:
  rmdformats::readthedown:
    highlight: kate
    toc_depth: 3
    self_contained: false
---


```{r knitr_init, echo=FALSE,warning=FALSE}
library(knitr)
library(rmdformats)
## Global options
options(max.print = "75")
opts_chunk$set(
  echo = TRUE,
  comment = "#>",
  dpi = 300,
  cache = FALSE
)
opts_knit$set(width = 75)
Sys.setenv("LANGUAGE"="EN")
```

# Dependencies

This project is depended on R software, R packages, shell bash, Julia software and some Julia packages :

- [NeoEnrichment](https://github.com/wt12318/NeoEnrichment) - do neoantigen enrichment for this project.
- [tidyverse](https://www.tidyverse.org/) - tidy data
- [data.table](https://github.com/Rdatatable/data.table) - read and tidy data
- [survival](https://github.com/therneau/survival) - survival analysis 
- [survminer](https://github.com/kassambara/survminer) - plot survival fit
- [DT](https://cran.r-project.org/web/packages/DT/index.html) - show data table as a table in html
- [patchwork](https://github.com/thomasp85/patchwork) - arrange figures into complex compound figures
- [maftools](https://github.com/PoisonAlien/maftools) - summarize, Analyze and Visualize MAF files
- [ComplexHeatmap](https://github.com/jokergoo/ComplexHeatmap) - make heatmap
- [ezcox](https://github.com/ShixiangWang/ezcox) -  operate a batch of univariate or multivariate Cox models and return tidy result
- [ggcharts](https://github.com/thomas-neitmann/ggcharts) - plot pyramid bar plot
- parallel - Parallel Computing
- [Julia](https://julialang.org/) - do simulation
- knitr, rmdformats - used to compile this file

```{r lib3,echo=TRUE,eval=FALSE}
library(tidyverse)
library(ggpubr)
library(cowplot)
library(NeoEnrichment)
library(parallel)
library(survminer)
library(survival)
library(data.table)
library(patchwork)
library(ComplexHeatmap)
library(maftools)
library(ezcox)
library(ggcharts)
```

# Data download and preprocessing

```{r child = 'data_download_preprocessing.Rmd'}
```

# TCGA pancancer analysis

```{r child = 'tcga_pancancer_analysis.Rmd'}
```

# Immunotherapy dataset analysis

```{r child = 'immunotherapy_analysis.Rmd'}
```

# Supplementary analyses
```{r child= 'Supplementary_analysis.Rmd'}
```