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T Cell Activation and Clonal Selection

T Cell Activation and Clonal Selection

T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...

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Related Experiment Video

Updated: Aug 3, 2025

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

clevRvis: visualization techniques for clonal evolution.

Sarah Sandmann¹, Clara Inserte¹, Julian Varghese¹

¹Institute of Medical Informatics, University of Münster, Münster 48149, Germany.

|April 11, 2023

Summary

This summary is machine-generated.

clevRvis, a new R/Bioconductor package, simplifies clonal evolution analysis with innovative visualization tools like plaice plots for biallelic events. It aids in understanding tumor development and therapy effects, even with limited patient data.

Keywords:

biallelic events cancer cell fraction clonal evolution therapy effect tumor development visualization

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Characterizing Mutational Load and Clonal Composition of Human Blood

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Last Updated: Aug 3, 2025

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

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Characterizing Mutational Load and Clonal Composition of Human Blood

Characterizing Mutational Load and Clonal Composition of Human Blood

Published on: July 11, 2019

Area of Science:

Oncology
Bioinformatics
Computational Biology

Background:

Clonal evolution analysis integrates diverse data (karyotyping, sequencing, clinical).
Limited patient samples often hinder complete understanding of clonal development and therapy effects.
Analyzing biallelic events, crucial for disease course, is typically time-consuming.

Purpose of the Study:

Introduce clevRvis, an R/Bioconductor package for visualizing clonal evolution.
Provide user-friendly tools for analyzing tumor development and therapy effects.
Enable efficient inspection of biallelic events using novel visualization techniques.

Main Methods:

Developed clevRvis, an R/Bioconductor package with visualization techniques for clonal evolution.
Implemented plaice plots for allele-aware representation of biallelic events.
Included algorithms for time point interpolation and therapy effect estimation.

Main Results:

clevRvis offers unique plaice plots for visualizing biallelic events at a glance.
Analysis of public datasets demonstrated new insights into tumor development and therapy resistance.
Automatic algorithms provided valid approximations of tumor development between measured time points.

Conclusions:

clevRvis provides a novel, user-friendly approach to clonal evolution analysis.
The package facilitates deeper insights into tumor development.
Enhances the interpretation of complex genomic data in cancer research.