Limits...
Quantifying Distribution of Flow Cytometric TCR-Vβ Usage with Economic Statistics.

van der Geest KS, Abdulahad WH, Horst G, Lorencetti PG, Bijzet J, Arends S, van der Heiden M, Buisman AM, Kroesen BJ, Brouwer E, Boots AM - PLoS ONE (2015)

Bottom Line: By applying economic statistics, we calculated the Gini-TCR skewing index from the flow cytometric TCR-Vβ analysis.The Gini-TCR skewing index, which is a direct measure of TCR-Vβ distribution among T cells, allowed us to track subtle changes of the TCR repertoire among distinct populations of T cells.Application of the Gini-TCR skewing index to the flow cytometric TCR-Vβ analysis will greatly help to gain better understanding of the TCR repertoire in health and disease.

View Article: PubMed Central - PubMed

Affiliation: Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

ABSTRACT
Measuring changes of the T cell receptor (TCR) repertoire is important to many fields of medicine. Flow cytometry is a popular technique to study the TCR repertoire, as it quickly provides insight into the TCR-Vβ usage among well-defined populations of T cells. However, the interpretation of the flow cytometric data remains difficult, and subtle TCR repertoire changes may go undetected. Here, we introduce a novel means for analyzing the flow cytometric data on TCR-Vβ usage. By applying economic statistics, we calculated the Gini-TCR skewing index from the flow cytometric TCR-Vβ analysis. The Gini-TCR skewing index, which is a direct measure of TCR-Vβ distribution among T cells, allowed us to track subtle changes of the TCR repertoire among distinct populations of T cells. Application of the Gini-TCR skewing index to the flow cytometric TCR-Vβ analysis will greatly help to gain better understanding of the TCR repertoire in health and disease.

Show MeSH

Related in: MedlinePlus

Schematic overview showing the relation between T cell receptor (TCR) Vβ diversity, distribution and percentages.(A) Schematic drawing illustrating broad versus contracted TCR-Vβ diversity. (B) Schematic drawing illustrating distribution and proportional usage of TCR Vβ families when TCR-Vβ diversity is broad or contracted. (C) Schematic drawing illustrating distribution of income among people.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4414620&req=5

pone.0125373.g001: Schematic overview showing the relation between T cell receptor (TCR) Vβ diversity, distribution and percentages.(A) Schematic drawing illustrating broad versus contracted TCR-Vβ diversity. (B) Schematic drawing illustrating distribution and proportional usage of TCR Vβ families when TCR-Vβ diversity is broad or contracted. (C) Schematic drawing illustrating distribution of income among people.

Mentions: Here, we introduce economic statistics to improve the analysis of flow cytometric data on TCR-Vβ usage. We noticed that the distribution of TCR-Vβ families among T cells resembles the distribution of income among people (Fig 1A–1C). Economists typically study the distribution of income by constructing Lorenz curves and calculating the Gini index. The Gini index, with scores ranging from 0 to 100, is a direct measure of income distribution [7–9]. By applying the Gini index to the flow cytometric TCR-Vβ analysis, we could directly measure the distribution of 24 TCR-Vβ families among multiple, well-defined T cell subsets. In this context, low Gini index values indicated equal distribution of TCR-Vβ families (i.e. broad repertoire), whereas high values pointed to unequal distribution of TCR-Vβ families (i.e. repertoire skewing). Although the Gini index has been used in TCR sequencing studies [10,11], we here demonstrate that the Gini index, hence referred to as the Gini-TCR skewing index, also aids the analysis of flow cytometric data on TCR-Vβ usage. Importantly, the Gini-TCR skewing index allowed us to detect subtle changes of the TCR repertoire among multiple, well-defined T cell subpopulations.


Quantifying Distribution of Flow Cytometric TCR-Vβ Usage with Economic Statistics.

van der Geest KS, Abdulahad WH, Horst G, Lorencetti PG, Bijzet J, Arends S, van der Heiden M, Buisman AM, Kroesen BJ, Brouwer E, Boots AM - PLoS ONE (2015)

Schematic overview showing the relation between T cell receptor (TCR) Vβ diversity, distribution and percentages.(A) Schematic drawing illustrating broad versus contracted TCR-Vβ diversity. (B) Schematic drawing illustrating distribution and proportional usage of TCR Vβ families when TCR-Vβ diversity is broad or contracted. (C) Schematic drawing illustrating distribution of income among people.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4414620&req=5

pone.0125373.g001: Schematic overview showing the relation between T cell receptor (TCR) Vβ diversity, distribution and percentages.(A) Schematic drawing illustrating broad versus contracted TCR-Vβ diversity. (B) Schematic drawing illustrating distribution and proportional usage of TCR Vβ families when TCR-Vβ diversity is broad or contracted. (C) Schematic drawing illustrating distribution of income among people.
Mentions: Here, we introduce economic statistics to improve the analysis of flow cytometric data on TCR-Vβ usage. We noticed that the distribution of TCR-Vβ families among T cells resembles the distribution of income among people (Fig 1A–1C). Economists typically study the distribution of income by constructing Lorenz curves and calculating the Gini index. The Gini index, with scores ranging from 0 to 100, is a direct measure of income distribution [7–9]. By applying the Gini index to the flow cytometric TCR-Vβ analysis, we could directly measure the distribution of 24 TCR-Vβ families among multiple, well-defined T cell subsets. In this context, low Gini index values indicated equal distribution of TCR-Vβ families (i.e. broad repertoire), whereas high values pointed to unequal distribution of TCR-Vβ families (i.e. repertoire skewing). Although the Gini index has been used in TCR sequencing studies [10,11], we here demonstrate that the Gini index, hence referred to as the Gini-TCR skewing index, also aids the analysis of flow cytometric data on TCR-Vβ usage. Importantly, the Gini-TCR skewing index allowed us to detect subtle changes of the TCR repertoire among multiple, well-defined T cell subpopulations.

Bottom Line: By applying economic statistics, we calculated the Gini-TCR skewing index from the flow cytometric TCR-Vβ analysis.The Gini-TCR skewing index, which is a direct measure of TCR-Vβ distribution among T cells, allowed us to track subtle changes of the TCR repertoire among distinct populations of T cells.Application of the Gini-TCR skewing index to the flow cytometric TCR-Vβ analysis will greatly help to gain better understanding of the TCR repertoire in health and disease.

View Article: PubMed Central - PubMed

Affiliation: Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

ABSTRACT
Measuring changes of the T cell receptor (TCR) repertoire is important to many fields of medicine. Flow cytometry is a popular technique to study the TCR repertoire, as it quickly provides insight into the TCR-Vβ usage among well-defined populations of T cells. However, the interpretation of the flow cytometric data remains difficult, and subtle TCR repertoire changes may go undetected. Here, we introduce a novel means for analyzing the flow cytometric data on TCR-Vβ usage. By applying economic statistics, we calculated the Gini-TCR skewing index from the flow cytometric TCR-Vβ analysis. The Gini-TCR skewing index, which is a direct measure of TCR-Vβ distribution among T cells, allowed us to track subtle changes of the TCR repertoire among distinct populations of T cells. Application of the Gini-TCR skewing index to the flow cytometric TCR-Vβ analysis will greatly help to gain better understanding of the TCR repertoire in health and disease.

Show MeSH
Related in: MedlinePlus