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FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows
An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increa...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602902/ https://www.ncbi.nlm.nih.gov/pubmed/34804056 http://dx.doi.org/10.3389/fimmu.2021.768541 |
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author | White, Scott Quinn, John Enzor, Jennifer Staats, Janet Mosier, Sarah M. Almarode, James Denny, Thomas N. Weinhold, Kent J. Ferrari, Guido Chan, Cliburn |
author_facet | White, Scott Quinn, John Enzor, Jennifer Staats, Janet Mosier, Sarah M. Almarode, James Denny, Thomas N. Weinhold, Kent J. Ferrari, Guido Chan, Cliburn |
author_sort | White, Scott |
collection | PubMed |
description | An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increasing data complexity, but by and large, still conduct all analysis using traditional applications, predominantly FlowJo. To a large extent, this cuts domain experts off from the rapidly growing library of Single Cell Data Science algorithms available, curtailing the potential contributions of these experts to the validation and interpretation of results. To address this challenge, we developed FlowKit, a Gating-ML 2.0-compliant Python package that can read and write FCS files and FlowJo workspaces. We present examples of the use of FlowKit for constructing reporting and analysis workflows, including round-tripping results to and from FlowJo for joint analysis by both domain and quantitative experts. |
format | Online Article Text |
id | pubmed-8602902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86029022021-11-20 FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows White, Scott Quinn, John Enzor, Jennifer Staats, Janet Mosier, Sarah M. Almarode, James Denny, Thomas N. Weinhold, Kent J. Ferrari, Guido Chan, Cliburn Front Immunol Immunology An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increasing data complexity, but by and large, still conduct all analysis using traditional applications, predominantly FlowJo. To a large extent, this cuts domain experts off from the rapidly growing library of Single Cell Data Science algorithms available, curtailing the potential contributions of these experts to the validation and interpretation of results. To address this challenge, we developed FlowKit, a Gating-ML 2.0-compliant Python package that can read and write FCS files and FlowJo workspaces. We present examples of the use of FlowKit for constructing reporting and analysis workflows, including round-tripping results to and from FlowJo for joint analysis by both domain and quantitative experts. Frontiers Media S.A. 2021-11-05 /pmc/articles/PMC8602902/ /pubmed/34804056 http://dx.doi.org/10.3389/fimmu.2021.768541 Text en Copyright © 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology White, Scott Quinn, John Enzor, Jennifer Staats, Janet Mosier, Sarah M. Almarode, James Denny, Thomas N. Weinhold, Kent J. Ferrari, Guido Chan, Cliburn FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows |
title | FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows |
title_full | FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows |
title_fullStr | FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows |
title_full_unstemmed | FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows |
title_short | FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows |
title_sort | flowkit: a python toolkit for integrated manual and automated cytometry analysis workflows |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602902/ https://www.ncbi.nlm.nih.gov/pubmed/34804056 http://dx.doi.org/10.3389/fimmu.2021.768541 |
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