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Computational analyses of multiparametric flow cytometry data

Free 

Services do NOT include

The service provides only computational analyses, no experimental cost is included.

Possible Output

The service will provide automatic clustering of cells, and statistical analyses on the impact of different experimental conditions on the distribution of cells among clusters. The results will be provided both in graphical (pdf files) and tabular form (csv files).

Sample Requirements - input of users

FCS files

Lead Scientist

Donata Medaglini

Description of service

Computational tools will be employed for the analysis of multiparametric flow cytometry data. Classical two-dimensional scatter plots analysis cannot be sufficient for the multidimensional nature of the flow cytometric data, especially when many parameters are simultaneously combined for studying the phenotype, effector function and the polyfunctionality of activated immune cells. Computational tools will be employed to analyze, visualize and interpret large amounts of cell data in an automated and unbiased way. Multiparametric flow cytometry can be particularly suitable for deep analysis of both T and B responses after vaccination, allowing to measure the frequency, the phenotype and the functional features of antigen-specific cells. The automated analysis allows to identify, in an unbiased way, all the cellular phenotypes elicited by vaccination, including not only terminally differentiated cells but also transient stages of differentiation, thus providing important information on activation and developmental stage of immune cells. Computational analysis can provide a complete signature of the both the innate and adaptive immune responses elicited by a particular vaccine formulation, that can be hardly obtained with the classical bi-dimensional gating analysis.

Timeline 

 

2/4 weeks per experiment

Contact 

Simone Furini

simone.furini@unisi.it

0039 0577 585297

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