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Updated: Mar 14, 2026

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

Computational methods for trajectory inference from single-cell transcriptomics.

Robrecht Cannoodt^1,2,3,4, Wouter Saelens^1,2, Yvan Saeys^5,6

¹Data Mining and Modelling for Biomedicine group, VIB Inflammation Research Center, Ghent, Belgium.

European Journal of Immunology

|September 30, 2016

Summary

This summary is machine-generated.

Single-cell transcriptomics and trajectory inference algorithms reveal immune cell development pathways. These methods offer new insights into gene regulation and cell differentiation, paving the way for data-driven immunology research.

Keywords:

Bioinformatics Cell differentiation Single-cell transcriptomics

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Published on: October 25, 2018

Area of Science:

Immunology
Computational Biology
Genomics

Background:

Single-cell transcriptomics enables high-throughput, unbiased study of dynamic biological processes.
Unsupervised trajectory inference algorithms reconstruct cell developmental paths from heterogeneous cell mixtures.

Purpose of the Study:

To review strategies for trajectory inference in immunology.
To organize these methods into a common framework.
To highlight practical advantages and disadvantages of different approaches.

Main Methods:

Analysis of unsupervised trajectory inference algorithms.
Framework development for comparing methods.
Review of existing literature on trajectory inference applications in immunology.

Main Results:

A common framework for understanding trajectory inference methods.
Identification of practical advantages and disadvantages of various algorithms.
Overview of new insights into immune cell differentiation, gene regulation, and developmental wiring.

Conclusions:

Trajectory inference methods provide powerful tools for dissecting immune cell differentiation.
Further developments are needed for a global, data-driven approach to studying immune cell development.
This field holds significant promise for advancing immunological research.