Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immunology #cytofpub https://t.co/P3XaBuGOgo
Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline.
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Feb 2019 – Jul 2020Where it's discussed
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X / Twitter14 posts
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YouTube3 videos
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The discussions reflect the publication's impact by emphasizing its role in streamlining large-scale cytometry experiments; for instance, mentions of file size reduction techniques and benchmarking methods show technical engagement, while references to the online database and automated workflows highlight its potential to transform immune monitoring practices.
Most discussions acknowledge the publication's importance in advancing immune monitoring tools and automated workflows.
Posts demonstrate high curiosity about data storage, experimental techniques, and implications for research.
Comments include technical details, questions about benchmarking methods, and references to data analysis procedures, showing active participation.
The discussions highlight the potential of the database and pipeline to improve mass cytometry research and clinical applications, indicating a significant influence.
Abstract in brief
- The article describes the development of a standardized, automated workflow for large-scale mass cytometry experiments aimed at improving immune monitoring in clinical trials, including a two-step barcoding process and a cloud-based analysis platform.
- The workflow was tested on a large antibody screening using the LEGENDScreen kit, generating detailed data for 350 antibodies across multiple cell subsets, which confirmed known immune system trends and identified potential new markers like those for MAIT cells.
- The study also examined how fixing cells affects staining results, finding that fixation can either increase or decrease marker signals, and produced an online database to help researchers design and interpret mass cytometry experiments more effectively.]
Top posts
Most liked on X and BlueskyDevelopment of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline #cytofpub @BioLegend #LEGENDscreen https://t.co/Q97OQ6C39E
How do we benchmark automated tools for labeling the different cell subsets? Here is one of the synthetic data sets that Astrolabe uses when testing our platform. https://t.co/BNM2u3kCoi #Cytometry #CyTOF #ImmuneMonitoring #FlowJo
Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/AUoSoEfGfm #biorxiv_immuno
Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/yG4WbPT4TH #bioRxiv
RT @ManchesterCytof: Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immuno…
All mentions
Reducing Size of Mass Cytometry FCS Files Using Data Processing Techniques
Passing a mass cytometry FCS file through an R or Matlab script can reduce its size by over 50%. This presentation discusses the 'OTHER' section in FCS files and explains why some data can be safely removed without…
Impact of PCA on Data Preprocessing in Bioinformatics Analysis
Principal component analysis (PCA) is frequently used as a preprocessing step in bioinformatics algorithms. This video discusses PCA's effects on data, especially regarding pairwise distances, using data from a recent…
Benchmarking Automated Cell Subset Labeling in Single-Cell Data Analysis
How do we benchmark automated tools for labeling the different cell subsets? This video discusses the use of synthetic datasets to evaluate Astrolabe's platform, highlighting its effectiveness in analyzing single-cell…
Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline. by Amir ED, Lee B, Badoual P, Gordon M, Guo XV, Merad M, Rahman AH https://t.co/RgzhqzHj4E
I've been seeing a lot of file transfer issues with #CyTOF data over the past month. Just a reminder that you can shrink the file size by 66%, learn more here https://t.co/SOmNv7x3x3 #SingleCells #MassCytometry
Passing a #MassCytometry FCS file through an R script, Matlab script, or other software will shrink its size by over 50%. I recorded a brief video where I explain why this happens and the ramifications for your experiment and FCS data storage: https://t.co/3Joq54Uv7h
How do we benchmark automated tools for labeling the different cell subsets? Here is one of the synthetic data sets that Astrolabe uses when testing our platform. https://t.co/BNM2u3kCoi #Cytometry #CyTOF #ImmuneMonitoring #FlowJo
RT @ManchesterCytof: Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immuno…
RT @ManchesterCytof: Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immuno…
RT @ManchesterCytof: Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immuno…
Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immunology #cytofpub https://t.co/P3XaBuGOgo
Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/ZMh26iNiji
RT @ManchesterCytof: Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline #cytofpub @BioLegend…
Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline #cytofpub @BioLegend #LEGENDscreen https://t.co/Q97OQ6C39E
Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/9XAeChVQXa
Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/AUoSoEfGfm #biorxiv_immuno
Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/yG4WbPT4TH #bioRxiv