SCGEATOOL :: Single-Cell Gene Expression Analysis Tool

Standalone Application Running on Windows Machines That Do Not Have MATLAB Installed.

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About

Brilliant Interactive Tool to Give Complete Control Over Single-Cell Data Points.

SCGEATOOL is a lightweight and blazing fast desktop application that provides interactive visualization functionality to analyze single-cell transcriptomic data. SCGEATOOL allows you to easily interrogate different views of your scRNA-seq data to quickly gain insights into the underlying biology. SCGEATOOL is a pre-compiled standalone application developed in MATLAB. Pre-compiled standalone releases are meant for those environments without access to MATLAB licenses. Standalone releases provide access to all of the functionality of the standard MATLAB scGEAToolbox encapsulated in a single application. SCGEATOOL is open-sourced to allow you to experience the added flexibility and speed of the MATLAB environment when needed.

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Features

Main Features

There are many features of SCGEATOOL as an end-to-end desktop application for single-cell transcriptome analysis.

All Essential Functions

With simple clicks, you can explore data with user-friendly interfaces and access updated functions for all essential tasks in single-cell transcriptome analysis.

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Scalable 3D Visualization

SCGEATOOL is optimized to visualize hundreds of thousands of single cells with MATLAB's high-quality interactive techniques, helping you to transform raw in-house data into insights.

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Versatile Data Integration

SCGEATOOL supports a wide range of cross-study analyses and data integration to deepen your biological understanding. Public scRNA-seq data in the GEO database can be imported without programming knowledge.

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Free and Open-Source

Source code for generating the standalone application is available at the GitHub repository. You can also find relevant citing publications by visiting Google Scholar.

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Installation

Instructions for PC/Windows Installation

Step 1. Download MATLAB Runtime version 24.2 (R2024b)* and run the MATLAB Runtime installer†.

Step 2. Download the file SCGEATOOL_StandaloneApplication.zip (68.3 MB) and unzip it.

Step 3. To start SCGEATOOL simply double-click on the scgeatool.exe icon.

*Visit MATLAB Runtime website for more information.
†Admin privileges are required to install MATLAB Runtime.

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FAQ

Any Questions? Answered

SCGEATOOL is a standalone application running on Windows machines that do not have MATLAB installed. If your PC has MATLAB installed, you should run MATLAB and install scGEAToolbox. Click here to learn how.
SCGEATOOL is a highly interactive cell browser for single-cell data analysis. It has several unique functions cannot be found in any other single-cell data analysis tools. These functions include, for example, SC_SPLINEFIT, one of the best algorithms for identifying highly variable genes (HVGs), scTenifoldNet, a machine learning workflow for constructing and comparing single-cell gene regulatory networks (scGRNs), scTenifoldKnk, a virtual knockout (KO) method for gene function prediction, and scTenifoldXct, a semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs.
MATLAB OnlineTM provides access to MATLAB from any standard web browser. Wherever you have Internet access, you can use SCGEATOOL by click Run scgeatool.m in MATLAB Online.
Most of the users must have seen the security warning, when you try to run a file downloaded from the Internet or an executable file that is located in a Network shared folder. It usually occurs when the file like scgeatool.exe is not digitally signed. You can ignore this warning when you run SCGEATOOL.
SCGEATOOL does have an additional module that supports spatial transcriptomics data analysis. The module is not included in current release of SCGEATOOL. Please Contact Us for more information.
Testimonials

What our Users Say

For people like me who have little R coding experience, this software has made it much easier for analyzing our single cell data.

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Biao Cao

Shanghai Institute of Nutrition and Health

I am enjoying the software a lot. It works pretty good! I really like the 3d-t-SNE that you made. This is so intuitive and nice.

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Munemasa Mori

Columbia University

Our members are so impressed. It's a really convient, powerful and highly interactive software!

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Ken Muneoka

Texas A&M University

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Veterinary Research Building, 588 Raymond Stotzer Pkwy, Texas A&M University, College Station, TX 77843

How Can We Help?

https://cailab-tamu.github.io/

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