Exvar: An R Package for Gene Expression and Genetic Variation Data Analysis and Visualization

Table of Contents

1. Motivation
2. About Exvar
3. Supported Species
4. Installation
5. Functions
6. License
7. Contact
8. Citation
9. Contributors

Motivation

RNA sequencing data manipulation workflows are complex and require various skills and tools. This creates the need for user-friendly and integrated genomic data analysis and visualization tools.

We developed a novel R package using multiple R packages to perform gene expression analysis and genetic variant calling from RNA sequencing data. The package could be used to analyze eight species’ data. Multiple public datasets were analyzed using the developed package to validate the pipeline for all the supported species.

About Exvar

The Exvar R package performs gene expression and genetic variats (SNPs, Indels, and CNVs) data analysis and visualization.

It is developed to facilitate and minimize the skills required for the genetic expression and variants calling. It includes 9 functions, providing an easy biologist-friendly workflow.

Supported Species

It could be used to analyze data from eight species including:

* Homo Sapiens (19, 37, and 38)

* Mus Musculus

* Arabidopsis Thaliana

* Drosophila Melanogaster

* Danio rerio

* Rattus norvegicus

* Caenorhabditis elegans  

* and Saccharomyces Cerevisiae.

Limitations:

Function/Species	processfastq	counts	expression	callsnp	callcnv	callindel	vizexp	vizsnp	vizcnv
Homo Sapiens	✓	✓	✓	✓	✓	✓	✓	✓	✓
Mus Musculus	✓	✓	✓	✓	✗	✓	✓	✓	✓
Arabidopsis Thaliana	✓	✓	✓	✓	✗	✓	✓	✓	✗
Drosophila Melanogaster	✓	✓	✓	✓	✗	✓	✓	✓	✓
Danio rerio	✓	✓	✓	✓	✗	✓	✓	✓	✓
Rattus norvegicus	✓	✓	✓	✓	✗	✓	✓	✓	✓
Caenorhabditis elegans	✓	✓	✓	✓	✗	✓	✓	✓	✗
Saccharomyces Cerevisiae	✓	✓	✓	✓	✗	✓	✓	✓	✓

Installation

The package could be installed as follows:

install.packages("devtools")

library(devtools)

devtools::install_github("omicscodeathon/Exvar/Package")

library(Exvar)

Functions

The package consists of 6 data analysis functions (processfastq(); counts(); expression(); callsnp(); callcnv(); and callindel()), 3 data visualization functions (vizexp(), vizsnp(), and vizcnv()), and a requirement() function is also provided to install all the dependencies. The list of functions and their roles are represented in Table 1.

Function	Role	Input	Output
requirement()	Install required packages	-	-
processfastq()	Preprocess fastq files	Fastq files	BAM files
counts()	Gene count analysis	BAM files	CSV file
expression()	Identify DEGs	BAM files	CSV file
callsnp()	SNP calling	BAM files	VCF files
callcnv()	CNV calling	BAM files	CSV file
callindel()	Indel calling	BAM files	VCF files
vizexp()	Analyze and visualize gene expression	CSV file	Interactive interface
vizsnp()	Analyze and visualize SNP data	VCF files	Interactive interface
vizcnv()	Analyze and visualize CNV data	CSV file	Interactive interface

Operating system :

• Linux for the processfastq(), counts(), expression(), callsnp(), callcnv(), and callindel() functions

• The visualization functions vizexp(), vizsnp(), and vizcnv() are platform-independent.

Programming language: R 4.2.1

Requirements:

The RAM and CPU requirements differ according to the analyzed data size. For Human whole genome data 16 CPUs and 65 GB RAM are required.

License

Artistic license 2.0 Any restrictions to use by non-academics: None.

Citation

Ben Aribi, H., Dixon, I., Abassi, N., & Awe, O. I. (2024). Exvar: An R Package for Gene Expression and Genetic Variation Data Analysis and Visualization. Zenodo. https://doi.org/10.5281/zenodo.13459761

Contributors

• Hiba Ben Aribi, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia.

• Imraan Dixon, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.

• Najla Abassi, Higher Institute of Biotechnology Sidi Thabet, Manouba University, Tunisia.

• Olaitan I. Awe, African Society for Bioinformatics and Computational Biology, Cape Town, South Africa.