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Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...

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Related Experiment Video

Updated: Jun 3, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

tagtango: an application to compare single-cell annotations.

Bernat Bramon Mora^1,2,3, Helen Lindsay^1,2,3, Antonin Thiébaut^1,2,3

¹Biomedical Data Science Center, Lausanne University Hospital, Vaud 1005, Switzerland.

Bioinformatics (Oxford, England)

|January 11, 2025

Summary

This summary is machine-generated.

tagtango is a new R package and web application for comparing single-cell clusters and annotations. It provides an interactive platform to explore biological differences across groups using various visualizations.

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Last Updated: Jun 3, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Published on: March 1, 2017

Area of Science:

Computational Biology
Bioinformatics
Genomics

Background:

Single-cell data analysis generates complex datasets requiring robust comparison methods.
Evaluating different clustering and annotation strategies is crucial for accurate biological interpretation.

Purpose of the Study:

To introduce tagtango, an R package and web application for intuitive comparison of single-cell clusters and annotations.
To provide researchers with a tool for exploring similarities and differences between various analytical approaches.

Main Methods:

Development of an R package and a web application.
Integration of interactive visualizations for data exploration.
Leveraging single-cell data analysis techniques.

Main Results:

tagtango offers a user-friendly, portable platform for cross-OS compatibility.
Facilitates the dissection of biological differences across cell groups.
Simplifies the comparison of diverse clustering and annotation methods.

Conclusions:

tagtango enhances the comparative analysis of single-cell data.
Provides an accessible tool for researchers in computational biology and genomics.
Supports robust interpretation of single-cell clustering and annotation results.