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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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WebSEQ: A New Tool for Democratizing Omics Data Sharing.

Shane A Liddelow¹, Ye Zhang², Steven A Sloan³

¹Neuroscience Institute, NYU Grossman School of Medicine, New York City, New York, USA.

|December 26, 2024

Summary

Researchers can now easily share and explore omics data, including transcriptomic, proteomic, and metabolomic datasets, using a new free online tool. This platform requires no coding, making complex molecular data analysis accessible for advancing neuroscience research.

Keywords:

data sharing glia lipidomics omics proteomics rnaseq

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Last Updated: Jun 4, 2025

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Published on: May 9, 2017

Area of Science:

Neuroscience
Bioinformatics
Data Science

Background:

Omics datasets (transcriptomic, proteomic, metabolomic) are rapidly generated but difficult to share and analyze.
Current public data repositories often lack user-friendly interfaces for data exploration.
Researchers face challenges in integrating and interpreting diverse omics data.

Purpose of the Study:

To present a free, online, user-friendly platform for sharing analyzed omics data.
To enhance the accessibility of molecular data for the scientific community.
To facilitate the exploration of transcriptomic, proteomic, and metabolomic data without requiring coding expertise.

Main Methods:

Development of a free, web-based tool for omics data sharing.
The tool accepts basic data spreadsheets, requiring no prior computational knowledge.
Implementation of a searchable and user-friendly interface for data exploration.

Main Results:

A functional online platform for sharing basic omics data has been established.
The tool enables users to explore transcriptomic, proteomic, and metabolomic datasets.
No coding or advanced computational skills are necessary to utilize the platform.

Conclusions:

Accessible omics data platforms are crucial for advancing neuroscience research.
This tool democratizes the exploration of molecular data, supporting glial diversity and function studies.
Simplified data sharing and analysis will accelerate scientific discovery in molecular biology and neuroscience.