README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
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)
```

# Cancer Personalized Drug Recommendation (CPDR)

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A recommendation tool of personalized drugs for patients with cancer by reversing individual disease signatures

## Installation

Before library installation install required Bioconductor and CRAN packages through this code:

``` r
bioconductor_packages=c('edgeR','RUVSeq','DESeq2','limma','rhdf5')

#For R version 3.5> use BiocManager to install required bioconductor packages: 
if (length(setdiff(bioconductor_packages, rownames(installed.packages()))) > 0) {
  if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
  BiocManager::install(setdiff(bioconductor_packages, rownames(installed.packages())))
}

packages=c('magrittr','dplyr','ggplot2','doParallel','foreach','Rfast','data.table')
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
  install.packages(setdiff(packages, rownames(installed.packages())))  
}

```
Now you can install the development version of CPDR with:

``` r
install.packages('devtools')
devtools::install_github("AllenSpike/CPDR")

```
## Additional data
By default, CPDR uses LINCS_978 from octad.db. To acquire reliable results, It is suggested to download the LINCS_all_processed data (6.5Gb) manually from https://zenodo.org/record/5880026#.YgZos9--uUl.

## Example
The vignette shows the usecase of screening effective compounds targeting individual patient with colorectal cancer.