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VariantSurvival: A tool to identify genotype-treatment response

Table of Content

  1. About VariantSurvival
    1.1 Installation
    1.2 Running the demo
    1.3 Running your data analysis
  2. Citing
  3. The developers team
  4. Help

About VariantSurvival

We present VariantSurvival, a lightweight application to visualize genotype-treatment response. The R application launches a dashboard to browse variant abundances and survival statistics for neurological diseases and corresponding target genes. VariantSurvival requires as input a set of annotated structural variants in the standard Variant Call Format (VCF) and a file of tabular metadata about the clinical trial or cohorts.

Installation

The application is installed via the R programming language using the following commands. First, the devtools R package is required to download VariantSurvival from its codebase. If you don't have devtools installed in your active R environment use

install.packages('devtools') #install devtools package
library(devtools) #activate devtools package

Now VariantSurvival itself can be installed (downloaded and activated) via

devtools::install_github("collaborativebioinformatics/VariantSurvival/VariantSurvival_package")
library(VariantSurvival)

Note that all dependencies will be installed automatically when installing VariantSurvival. After a successful installation the currently installed software version can be retrieved via

packageVersion("VariantSurvival")

Running the demo

After following the installation instructions the VariantSurvival dashboard can be launched with demo data via

VariantSurvival::VariantSurvival(demo=TRUE)

Running your data analysis

To launch the dashboard with your own clinical data two input files have to be provided. One required input is a VCF file with a set of gene-annotated structural variants across the entire study cohort. We have compiled a dedicated manual page on how to prepare your VCF file for VariantSurvival with instructions and recommendations how to merge and annotate VCF files.

The second strictly required input file is a tabular metadata Excel sheet. The minimal set of required columns for the quantitavite and survival analysis is

Column name Type Encoding
Patient IDs [string] Matching the sample names of the VCF file
Time factor [continuous] Time since onset in days or years
Trial group [binary] Treatment / control
Survival state [binary] Deceased / alive

Given a VCF file my_variant_file.vcf and an Excel sheet my_metadata_file.xlsx the dashboard is launched passing both files as function paramters.

VariantSurvival::VariantSurvival(vcffile="my_variant_file.vcf", metadatafile= "my_metadata_file.xlsx")

Citing

If you use VariantSurvival, please cite this journal publication

  • Krannich T, Sarrias MH, Ben Aribi H, Shokrof M, Iacoangeli A, Al-Chalabi A, Sedlazeck FJ, Busby B and Al Khleifat A (2023) VariantSurvival: a tool to identify genotype–treatment response. Front. Bioinform. 3:1277923. doi: 10.3389/fbinf.2023.1277923

The developers team

  • Ahmad Al Khleifat Twitter URL
  • Thomas Krannich Twitter URL
  • Hiba Ben Aribi Twitter URL
  • Marina Herrera Sarrias
  • Moustafa Shokrof Twitter URL

Help

For questions about VariantSurvival and bug reports please refer to the GitHub issues section of this repository.

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VariantSurvival a Shiny app/ R package to identify genotype-treatment response

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