https://github.com/cbg-ethz/perturbatr

Analysis of high-throughput genetic perturbation screens in R.
https://github.com/cbg-ethz/perturbatr

biological-data-analysis computational-biology mixed-models r statistical-inference

Last synced: about 2 months ago
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Analysis of high-throughput genetic perturbation screens in R.

• Host: GitHub
• URL: https://github.com/cbg-ethz/perturbatr
• Owner: cbg-ethz
• License: gpl-3.0
• Created: 2016-07-17T18:19:45.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2020-02-09T20:57:12.000Z (almost 5 years ago)
• Last Synced: 2024-08-09T00:21:48.270Z (5 months ago)
• Topics: biological-data-analysis, computational-biology, mixed-models, r, statistical-inference
• Language: R
• Homepage: https://bioconductor.org/packages/release/bioc/html/perturbatr.html
• Size: 31.2 MB
• Stars: 2
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Code of conduct: code-of-conduct.md

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README

        
# perturbatr 

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Analysis of high-throughput gene perturbation screens in R.

## Introduction

`perturbatr` does stage-wise analysis of large-scale genetic

perturbation screens for integrated data sets consisting of multiple screens.

For multiple integrated perturbation screens a hierarchical model that

considers the variance between different biological conditions is fitted.

That means that we first estimate relative effect sizes for all genes.

The resulting hit lists is then further extended using a network

propagation algorithm to correct for false negatives. and positives.

```{r}

data(rnaiscreen)

graph <- readRDS(

  system.file("extdata", "graph_file.tsv", package = "perturbatr"))

frm   <- Readout ~ Condition +

                   (1|GeneSymbol) + (1|Condition:GeneSymbol) +

                   (1|ScreenType) + (1|Condition:ScreenType)

ft    <- hm(rnaiscreen, formula = frm)

diffu <- diffuse(ft, graph=graph, r=0.3)

plot(diffu)

```

## Installation

You can install and use `perturbatr` either as an `R` library from [Bioconductor](https://doi.org/doi:10.18129/B9.bioc.perturbatr),

or by downloading the [tarball](https://github.com/cbg-ethz/perturbatr/releases).

If you want to use the **recommended** way using Bioconductor just call:

```r

if (!requireNamespace("BiocManager", quietly=TRUE))

  install.packages("BiocManager")

BiocManager::install("perturbatr")

  

library(perturbatr)

```

from the R-console.

Installing the package using the downloaded tarball works like this:

```bash

  R CMD install 

```

where `perturbatr.tar.gz` is the downloaded tarball.

## Documentation

Load the package using `library(perturbatr)`. We provide a vignette for the package that can be called using: `vignette("perturbatr")`.

## Author

* Simon Dirmeier [email protected]