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Genomics

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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GENAVi: a shiny web application for gene expression normalization, analysis and visualization.

Alberto Luiz P Reyes¹, Tiago C Silva¹, Simon G Coetzee¹

¹Center for Bioinformatics and Functional Genomics, Department of Biomedical Science, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.

|October 18, 2019

Summary

This summary is machine-generated.

GENAVi offers a user-friendly graphical interface for RNA-Seq data analysis, making complex gene expression normalization and differential expression analysis accessible to biologists without programming skills.

Keywords:

Differential expression GUI Next generation sequencing Normalization RNA-seq Shiny Visualization

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Published on: December 22, 2017

Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Next-generation sequencing (NGS) generates large genomic datasets.
User-friendly tools for analyzing and visualizing NGS data lag behind data generation.
Biologists face challenges in selecting and applying bioinformatics pipelines without programming expertise.

Purpose of the Study:

To develop GENAVi (Gene Expression Normalization Analysis and Visualization), a graphical user interface (GUI) tool.
To provide accessible RNA-Seq data analysis for scientists without bioinformatics expertise.
To enable normalization, differential expression analysis, and visualization of gene expression data.

Main Methods:

Developed GENAVi as a GUI-based web application using Shiny.
Integrated Bioconductor packages for RNA-Seq analysis.
Included a panel of 20 common cancer cell lines and options for user data integration.
Provided local installation options for scalability.

Main Results:

GENAVi enables user-friendly normalization and differential expression analysis (DEA) of RNA-Seq data.
The tool allows visualization of expression across samples, sample clustering, and principal component analysis.
Users can perform DEA and gene set enrichment analysis with clear reporting for reproducible results.
GENAVi offers multiple normalization methods and an intuitive interface.

Conclusions:

GUI-based tools like GENAVi enhance the accessibility of complex bioinformatics workflows for biologists.
GENAVi improves upon existing RNA-Seq analysis tools with its user-friendly interface and comprehensive features.
This application serves as a convenient platform for gene expression data analysis and visualization for non-bioinformaticians.