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krsa

An R package for analyzing PamGene kinome array data

https://github.com/cogdisreslab/krsa

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    Found .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (16.1%) to scientific vocabulary

Keywords

r r-package rstats
Last synced: 10 months ago · JSON representation

Repository

An R package for analyzing PamGene kinome array data

Basic Info
Statistics
  • Stars: 4
  • Watchers: 1
  • Forks: 5
  • Open Issues: 23
  • Releases: 16
Topics
r r-package rstats
Created over 5 years ago · Last pushed 10 months ago
Metadata Files
Readme License Codemeta

README.Rmd 

---
title: "Intro"
author: "Khaled Alganem"
output:
  md_document:
    variant: markdown_github
---

# KRSA: Kinome Random Sampling Analyzer



[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
[![Build Status](https://github.com/CogDisResLab/KRSA/actions/workflows/rworkflows.yml/badge.svg)](https://github.com/CogDisResLab/KRSA/actions/workflows/rworkflows.yml)
[![pkgdown](https://github.com/CogDisResLab/KRSA/actions/workflows/pkgdown.yml/badge.svg)](https://github.com/CogDisResLab/KRSA/actions/workflows/pkgdown.yml)
[![Repo Status](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)



KRSA is a package designed to analyze the high throughput kinase activity
data generated by the PamGene's PamChip platform. The primary purpose of this package
is to implement a novel way to predict upstream kinase activity based on the
peptide phosphorylation data. In addition to the implementation of the KRSA
algorithm, this package also provides a few convenience methods that allow
users to load, analyze and visualize the PamChip data.

## Installation

This package is available through [CDRL](https://cdrl-ut.org)'s `r-universe` repository.
The easiest way to install a stable version is to use that version.

```r
install.packages("KRSA", repos = c("https://cogdisrelab.r-universe.dev", "https://cloud.r-project.org"))
```

To install the development version of the package, you can install directly from
the GitHub repository.

```r
if (!requireNamespace("remotes", quietly = TRUE)) {
  install.packages("remotes")
}

remotes::install_github("CogDisResLab/KRSA")
```

## KRSA 

Kinome Random Sampling Analyzer, or KRSA, is an R Shiny application that automates many of the steps required to analyze [PamChip](https://pamgene.com/technology/) datasets, including peptide filtering, random sampling, heatmap generation, and kinase network generation. This new software makes analyzing kinome array datasets accessible and eliminates much of the human workload that the previous method required. More importantly, KRSA represents the results in a bigger biological context by visualizing altered kinome signaling networks instead of individual kinases.

More info on the PamChip and the PamStation12 platform can be found here: [PamGene](https://pamgene.com/technology/)

## Package Website



## Workflow

![KRSA Workflow](man/figures/workflow.png)

## Random Sampling Approach

###### Running Random Sampling



  




 


###### Calculating Mean, Standard Deviations, and Z Scores



  







## Input Files

The user-supplied kinase-peptide association file and the raw kinome array data file are selected as input. The kinase-peptide associations should be based on the known/predicted interactions found in databases like GPS 3.0 and Kinexus Phosphonet. Expected inputs should be formatted as shown in the example files: vignettes/data_files/example_Median_SigmBg.txt

Owner

  • Name: Cognitive Disorders Research Lab
  • Login: CogDisResLab
  • Kind: organization
  • Email: contact@cdrl-ut.org
  • Location: United States of America

CodeMeta (codemeta.json) 

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GitHub Events

Total
  • Release event: 1
  • Delete event: 27
  • Push event: 30
  • Pull request event: 61
  • Fork event: 1
  • Create event: 33
Last Year
  • Release event: 1
  • Delete event: 27
  • Push event: 30
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Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 1
  • Total pull requests: 23
  • Average time to close issues: about 3 hours
  • Average time to close pull requests: about 4 hours
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 13
  • Bot issues: 1
  • Bot pull requests: 23
Past Year
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  • Pull requests: 23
  • Average time to close issues: about 3 hours
  • Average time to close pull requests: about 4 hours
  • Issue authors: 1
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  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 13
  • Bot issues: 1
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Top Authors
Issue Authors
  • AliSajid (3)
  • renovate[bot] (2)
Pull Request Authors
  • renovate[bot] (67)
  • AliSajid (12)
Top Labels
Issue Labels
enhancement (3) bug (1)
Pull Request Labels
dependencies (66) renovate (66) enhancement (1)

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
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  • pheatmap * imports
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  • rlang * imports
  • stats * imports
  • stringr * imports
  • tibble * imports
  • tidyr * imports
  • utils * imports
  • furrr * suggests
  • gt * suggests
  • knitr * suggests
  • markdown * suggests
  • rmarkdown * suggests
  • tidyverse * suggests
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