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---
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-",
out.width = "100%"
)
```
# KINNET
<!-- badges: start -->
<!-- [](https://zenodo.org/badge/latestdoi/301042598) -->
[](https://github.com/AliSajid/KINNET/issues)
[](https://github.com/AliSajid/KINNET/network)
[](https://github.com/AliSajid/KINNET/stargazers)
[]()
[]()
[](https://github.com/AliSajid/KINNET/blob/main/LICENSE)
[](https://travis-ci.com/AliSajid/KINNET)
<!-- badges: end -->
This package provides the functionality to process PamGene's PamChip
Data Output and generate kinase interaction networks from that.
This project uses a bayesian algorithm to generate bayesian networks for
defining dependence relationships between peptide sequences in the PamChip data.
It then uses a novel kinase assignment method to assign upstream kinases to each
peptide which is then output as a graph.
## Installation
You can install the released version of KINNET from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("KINNET")
```
You can install the latest development version of KINNET from [Github]() with:
``` r
remotes::install_github("AliSajid/KINNET")
```
## Example
This is a basic example which shows you how to solve a common problem:
```{r example}
#library(KINNET)
## basic example code
```