Connect with us

Software

GIANT: A New Tool for Transcriptomic Data Analysis

Published

on

Transcriptomic data analysis

Transcriptomic data analysis is an important requirement in biomedical research. The bioinformatics tools available for transcriptomic data analysis provide a user-friendly interface that is easily accessible by the experimental biologists as well. A new tool called GIANT-Galaxy-based tool for Interactive ANalysis of Transcriptomic data has been developed by Vandel et al., [1].

GIANT is a set of tools allowing researchers to analyze transcriptomic data from microarray or RNA-seq analyses [1]. It consists of different modules facilitating the easy selection of tools for a particular analysis. The source code of the GIANT is freely downloadable on Github (https://github.com/juliechevalier/GIANT). The Galaxy tool suite is available on the Galaxy Main Tool Shed (https://toolshed.g2.bx.psu.edu; name:suite_giant; owner:vandelj).

How GIANT works?

GIANT takes raw data from microarray or RNA-seq. Depending upon that, it selects methodology to process the data.

  • Firstly, it subjects the input data to a quality check.
  • In the next step, it leads to normalization including differential analysis in both the cases (microarray and RNA-seq).
  • After differential analysis, the data is subjected to another quality check. It is highly recommended [1].
  • After that, it generates volcano plots and heatmaps, performs clustering and GSEA formatting as per the user requirements.

GIANT suite consists of various adjustable parameters to improve the analysis and visualization of transcriptomic data. As an output, it provides interactive plots, tabular results, and easy visualization and sharing of the data. For further reading, click here.


References

  1. Vandel, J., Gheeraert, C., Staels, B., Eeckhoute, J., Lefebvre, P., & Dubois-Chevalier, J. (2020). GIANT: Galaxy-based tool for Interactive ANalysis of Transcriptomic data. Scientific Reports.

Tariq is founder of Bioinformatics Review and CEO at IQL Technologies. His areas of expertise include algorithm design, phylogenetics, MicroArray, Plant Systematics, and genome data analysis. If you have questions, reach out to him via his homepage.

Software

How to calculate binding pocket volume using PyVol plugin in PyMol?

Published

on

How to calculate binding pocket volume using PyVol plugin in PyMol?

Previously, we provided a tutorial for PyVol plugin [1] installation. In this article, we will calculate the binding pocket volume of protein using the same plugin in PyMol [2]. (more…)

Continue Reading

Software

How to generate electron density map using Pymol?

Published

on

How to generate electron density map using Pymol?

Electron density maps are available for most of the protein structures in PDB. Therefore, in this article, we are using PDB to generate electron density maps in Pymol.

(more…)

Continue Reading

Software

Installing PyVOL plugin in Pymol on Ubuntu (Linux).

Published

on

Installing PyVOL plugin in Pymol on Ubuntu (Linux).

PyVOL [1] is an excellent plugin of Pymol [2] for pocket visualization of proteins. In this article, we will install the PyVOL plugin in Pymol on Ubuntu. (more…)

Continue Reading

LATEST ISSUE

ADVERT