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FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data

A new software package called flowFP for the analysis of flow cytometry data is introduced. The package, which is tightly integrated with other Bioconductor software for analysis of flow cytometry, provides tools to transform raw flow cytometry data into a form suitable for direct input into convent...

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Detalles Bibliográficos
Autores principales: Rogers, Wade T., Holyst, Herbert A.
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2777013/
https://www.ncbi.nlm.nih.gov/pubmed/19956416
http://dx.doi.org/10.1155/2009/193947
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author Rogers, Wade T.
Holyst, Herbert A.
author_facet Rogers, Wade T.
Holyst, Herbert A.
author_sort Rogers, Wade T.
collection PubMed
description A new software package called flowFP for the analysis of flow cytometry data is introduced. The package, which is tightly integrated with other Bioconductor software for analysis of flow cytometry, provides tools to transform raw flow cytometry data into a form suitable for direct input into conventional statistical analysis and empirical modeling software tools. The approach of flowFP is to generate a description of the multivariate probability distribution function of flow cytometry data in the form of a “fingerprint.” As such, it is independent of a presumptive functional form for the distribution, in contrast with model-based methods such as Gaussian Mixture Modeling. FlowFP is computationally efficient and able to handle extremely large flow cytometry data sets of arbitrary dimensionality. Algorithms and software implementation of the package are described. Use of the software is exemplified with applications to data quality control and to the automated classification of Acute Myeloid Leukemia.
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spelling pubmed-27770132009-12-02 FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data Rogers, Wade T. Holyst, Herbert A. Adv Bioinformatics Research Article A new software package called flowFP for the analysis of flow cytometry data is introduced. The package, which is tightly integrated with other Bioconductor software for analysis of flow cytometry, provides tools to transform raw flow cytometry data into a form suitable for direct input into conventional statistical analysis and empirical modeling software tools. The approach of flowFP is to generate a description of the multivariate probability distribution function of flow cytometry data in the form of a “fingerprint.” As such, it is independent of a presumptive functional form for the distribution, in contrast with model-based methods such as Gaussian Mixture Modeling. FlowFP is computationally efficient and able to handle extremely large flow cytometry data sets of arbitrary dimensionality. Algorithms and software implementation of the package are described. Use of the software is exemplified with applications to data quality control and to the automated classification of Acute Myeloid Leukemia. Hindawi Publishing Corporation 2009 2009-09-24 /pmc/articles/PMC2777013/ /pubmed/19956416 http://dx.doi.org/10.1155/2009/193947 Text en Copyright © 2009 W. T. Rogers and H. A. Holyst. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Rogers, Wade T.
Holyst, Herbert A.
FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data
title FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data
title_full FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data
title_fullStr FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data
title_full_unstemmed FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data
title_short FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data
title_sort flowfp: a bioconductor package for fingerprinting flow cytometric data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2777013/
https://www.ncbi.nlm.nih.gov/pubmed/19956416
http://dx.doi.org/10.1155/2009/193947
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