Development of a Comprehensive Antibody Staining Database using a Standardized Analytics Pipeline

We propose a standardized workflow for the acquisition and analysis of large-scale mass cytometry experiments

Amir

2019

Scholarcy highlights

  • BioRxiv preprint doi: https://doi.org/10.1101/563742; this version posted May 2, 2019
  • Despite the well-developed ecosystem, there is no clear standard on how to run a large-scale mass cytometry study, and researchers are often forced to reinvent the wheel by designing experiments de novo with no clear guidance on best practices
  • Except for the batch effects identified by the Average overlap frequency QC, the data set was consistent across cell subsets and marker intensities
  • To validate and further explore the co-expression patterns of the markers identified in the screen, we independently stained a healthy donor peripheral blood mononuclear cell sample with a panel incorporating several of the differentially
  • We present a standardized workflow for the acquisition and analysis of large-scale immune monitoring studies using mass cytometry
  • The workflow provides a flexible framework that can be adapted to clinical trial immune monitoring or other large-scale experiments and greatly improve the quality, reproducibility, robustness and utility of mass cytometry data. We leveraged this standardized workflow as part of a comprehensive screen to establish the expression of 350 surface markers across all major circulating immune subsets at single cell resolution
  • This dataset represents an accessible and unbiased resource for assessing potential expression of various markers over a large range of immune subsets in healthy individuals and surveying the statistics in the entire data set reveals intriguing signals for potential expression of less-studied markers

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