A Web-Server of Cell Type Discrimination System

Anyou Wang,Qianchuan He,Yan Zhong,Yanhua Wang

doi:10.1155/2014/459064

Abstract

Discriminating cell types is a daily request for stem cell biologists. However, there is not a user-friendly system available to date for public users to discriminate the common cell types, embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), and somatic cells (SCs). Here, we develop WCTDS, a web-server of cell type discrimination system, to discriminate the three cell types and their subtypes like fetal versus adult SCs. WCTDS is developed as a top layer application of our recent publication regarding cell type discriminations, which employs DNA-methylation as biomarkers and machine learning models to discriminate cell types. Implemented by Django, Python, R, and Linux shell programming, run under Linux-Apache web server, and communicated through MySQL, WCTDS provides a friendly framework to efficiently receive the user input and to run mathematical models for analyzing data and then to present results to users. This framework is flexible and easy to be expended for other applications. Therefore, WCTDS works as a user-friendly framework to discriminate cell types and subtypes and it can also be expended to detect other cell types like cancer cells.

Highlights

Induced pluripotent stem cells and embryonic stem cells (ESCs) provide important resources for medical research and applications [1]
A user-friendly discriminant system to fill this task still remains to be further developed. Traditional approaches like those based on single antibody (e.g., OCT4) unlikely provide a satisfactory result due to their low sensitivity and the high similarity between Induced pluripotent stem cells (iPSCs) and ESCs [2]
Cluster analyses based on global gene expression signatures have been developed to discriminate somatic cells (SCs) from pluripotent cells (PCs) [3,4,5,6], including iPSCs and ESCs, but this system cannot be used to discriminate iPSCs and ESCs because the gene signatures are not consistently expressed across different cell lines and conditions [5,6,7] and clustering is associated with the low sensitivity in determining classification [8]

Summary

Instruction

Induced pluripotent stem cells (iPSCs) and embryonic stem cells (ESCs) provide important resources for medical research and applications [1]. A user-friendly discriminant system to fill this task still remains to be further developed Traditional approaches like those based on single antibody (e.g., OCT4) unlikely provide a satisfactory result due to their low sensitivity and the high similarity between iPSC and ESCs [2]. When appropriate biomarkers are applied, this system can discriminate SCs from PCs with 100% accuracy and can distinguish ESCs from iPSCs with an accuracy of 95% This system can even accurately discriminate the subtypes of cells, such as female and male iPSCs and fetal and adult SCs [9]. This system can be used as a framework for discriminating the three cell types and subtypes. We developed a web-server, WCTDS, to provide a user-friendly interface to allow users without any computer background to discriminate three cell types and their subtypes

Materials and Methods

Results and Discussion

13 Simulation 1 Simulation 2

Conclusion