ArticlePLoS computational biology2021
CytoPy: An autonomous cytometry analysis framework.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Navigating the Landscape of Cytometry-Based Single-Cell Proteomics: Quantification, Annotation, and Resources.International journal of molecular sciences · 2026Review
- A hand-operated microfluidic sample preparation-to-analysis workflow for simplifying the basophil activation test.Lab on a chip · 2025Article
- CAFE: an integrated web app for high-dimensional analysis and visualization in spectral flow cytometry.Bioinformatics (Oxford, England) · 2025Article
- CAFE: An Integrated Web App for High-Dimensional Analysis and Visualization in Spectral Flow Cytometry.bioRxiv : the preprint server for biology · 2024Article
- Conventional and unconventional T-cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients.Clinical and experimental immunology · 2024Article
- Proteome Mapping of the Human Pancreatic Islet Microenvironment Reveals Endocrine-Exocrine Signaling Sphere of Influence.Molecular & cellular proteomics : MCP · 2023Article
- ANPELA: Significantly Enhanced Quantification Tool for Cytometry-Based Single-Cell Proteomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- GeoWaVe: geometric median clustering with weighted voting for ensemble clustering of cytometry data.Bioinformatics (Oxford, England) · 2023Article
- AliGater: a framework for the development of bioinformatic pipelines for large-scale, high-dimensional cytometry data.Bioinformatics advances · 2023Article
- Unconventional T cells and kidney disease.Nature reviews. Nephrology · 2021Review
- FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows.Frontiers in immunology · 2021Article
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Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Cytometry analysis has seen a considerable expansion in recent years in the maximum number of parameters that can be acquired in a single experiment. In response to this technological advance there has been an increased effort to develop new computational methodologies for handling high-dimensional single cell data acquired by flow or mass cytometry. Despite the success of numerous algorithms and published packages to replicate and outperform traditional manual analysis, widespread adoption of these techniques has yet to be realised in the field of immunology. Here we present CytoPy, a Python framework for automated analysis of cytometry data that integrates a document-based database for a data-centric and iterative analytical environment. In addition, our algorithm-agnostic design provides a platform for open-source cytometry bioinformatics in the Python ecosystem. We demonstrate the ability of CytoPy to phenotype T cell subsets in whole blood samples even in the presence of significant batch effects due to technical and user variation. The complete analytical pipeline was then used to immunophenotype the local inflammatory infiltrate in individuals with and without acute bacterial infection. CytoPy is open-source and licensed under the MIT license. CytoPy is available at https://github.com/burtonrj/CytoPy, with notebooks accompanying this manuscript (https://github.com/burtonrj/CytoPyManuscript) and software documentation at https://cytopy.readthedocs.io/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.