Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline.

El-Ad David Amir, Brian Lee, Paul Badoual, Martin Gordon, Xinzheng V Guo, Miriam Merad, Adeeb H Rahman

July 2020

Synopsis of Social media discussions

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.

A
Agreement
 Moderate agreement

Most discussions acknowledge the publication's importance in advancing immune monitoring tools and automated workflows.

I
Interest
 High level of interest

Posts demonstrate high curiosity about data storage, experimental techniques, and implications for research.

E
Engagement
 Moderate level of engagement

Comments include technical details, questions about benchmarking methods, and references to data analysis procedures, showing active participation.

I
Impact
 High level of impact

The discussions highlight the potential of the database and pipeline to improve mass cytometry research and clinical applications, indicating a significant influence.

Social Mentions

YouTube

3 Videos

Twitter

14 Posts

Metrics

Video Views

845

Total Likes

19

Extended Reach

153,363

Social Features

17

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

Reducing Size of Mass Cytometry FCS Files Using Data Processing Techniques

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 losing critical information.

Astrolabe Diagnostics

October 16, 2019

588 views

Impact of PCA on Data Preprocessing in Bioinformatics Analysis

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 Frontiers paper. Contact us for single-cell data analysis support.

Astrolabe Diagnostics

October 29, 2019

209 views

Benchmarking Automated Cell Subset Labeling in Single-Cell Data Analysis

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 data for immune monitoring.

Astrolabe Diagnostics

October 2, 2019

48 views

  • NK papers
    @NK_papers (Twitter)

    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
    view full post

    July 17, 2020

  • Astrolabe Diagnostics, Inc.
    @astrolabediag (Twitter)

    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
    view full post

    June 25, 2020

  • Astrolabe Diagnostics, Inc.
    @astrolabediag (Twitter)

    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
    view full post

    October 16, 2019

  • Astrolabe Diagnostics, Inc.
    @astrolabediag (Twitter)

    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
    view full post

    October 2, 2019

    2

    1

  • Guojun Han
    @GuojunHan (Twitter)

    RT @ManchesterCytof: Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immuno…
    view full post

    July 6, 2019

    3

  • Ran Wei
    @RanWei_Biology (Twitter)

    RT @ManchesterCytof: Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immuno…
    view full post

    July 5, 2019

    3

  • Thomas Ashhurst
    @TomAsh_1 (Twitter)

    RT @ManchesterCytof: Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immuno…
    view full post

    July 2, 2019

    3

  • Cytof Manchester
    @ManchesterCytof (Twitter)

    Frontiers | Development of a Comprehensive Antibody Staining Database Using a Standardized Analytics Pipeline | Immunology #cytofpub https://t.co/P3XaBuGOgo
    view full post

    July 1, 2019

    4

    3

  • CMCA Cytometry
    @CMCACytometry (Twitter)

    Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/ZMh26iNiji
    view full post

    March 14, 2019

  • BIOCOM Africa
    @biocomafricarsa (Twitter)

    RT @ManchesterCytof: Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline #cytofpub @BioLegend…
    view full post

    March 5, 2019

    1

  • Cytof Manchester
    @ManchesterCytof (Twitter)

    Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline #cytofpub @BioLegend #LEGENDscreen https://t.co/Q97OQ6C39E
    view full post

    March 4, 2019

    2

    1

  • bxv_imm
    @bxv_imm (Twitter)

    Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/9XAeChVQXa
    view full post

    March 1, 2019

  • bioRxiv Immunology
    @biorxiv_immuno (Twitter)

    Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/AUoSoEfGfm #biorxiv_immuno
    view full post

    February 28, 2019

    1

  • bioRxiv
    @biorxivpreprint (Twitter)

    Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline https://t.co/yG4WbPT4TH #bioRxiv
    view full post

    February 28, 2019

Abstract Synopsis

  • 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.]