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Making the most of high‐dimensional cytometry data

Felix MD Marsh‐Wakefield, Andrew J Mitchell, Samuel E Norton, Thomas Myles Ashhurst, Julia KH Leman, Joanna M Roberts, Jessica E Harte, Helen M McGuire, Roslyn A Kemp
2021 Immunology and Cell Biology  
A plethora of analysis and visualisation tools and programmes are now available for both new and experienced users; however, the transition from low-dimensional to high-dimensional cytometry requires a  ...  In this article, we explain the concepts behind designing high-dimensional cytometry experiments and provide considerations for new and experienced users to design and carry out high-dimensional experiments  ...  ACKNOWLEDGMENTS We thank the Australia and New Zealand Society for Immunology and the Australasian Cytometry Society for providing funding to host a workshop to create this work.  ... 
doi:10.1111/imcb.12456 pmid:33797774 fatcat:fz5gabqd7bhitb3swqfzvgmwf4

A Cancer Biologist's Primer on Machine Learning Applications in High‐Dimensional Cytometry

Timothy J. Keyes, Pablo Domizi, Yu‐Chen Lo, Garry P. Nolan, Kara L. Davis
2020 Cytometry Part A  
for analyzing and interpreting cytometry data.  ...  Society for Advancement of Cytometry.  ...  flow cytometry or mass cytometry (for an example of this approach, see (35) ).  ... 
doi:10.1002/cyto.a.24158 pmid:32602650 fatcat:wuxhbmt65bbe5ghqsnzb2j52ni

Feature selection revisited in the single-cell era [article]

Pengyi Yang, Hao Huang, Chunlei Liu
2021 arXiv   pre-print
Feature selection techniques are essential for high-dimensional data analysis.  ...  We review their versatile application to a range of single-cell data types including those generated from traditional cytometry and imaging technologies and the latest array of single-cell omics technologies  ...  A key application of feature selection methods to flow and mass cytometry data has been for finding optimal protein markers for cell gating (105) .  ... 
arXiv:2110.14329v1 fatcat:fvliiws52ramrhyz53ijdlt73u

Feature selection revisited in the single-cell era

Pengyi Yang, Hao Huang, Chunlei Liu
2021 Genome Biology  
We review their application to a range of single-cell data types generated from traditional cytometry and imaging technologies and the latest array of single-cell omics technologies.  ...  AbstractRecent advances in single-cell biotechnologies have resulted in high-dimensional datasets with increased complexity, making feature selection an essential technique for single-cell data analysis  ...  Peer review information Barbara Cheifet was the primary editor of this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.  ... 
doi:10.1186/s13059-021-02544-3 pmid:34847932 pmcid:PMC8638336 fatcat:u62n34lpgzh43mu7mszwm63ls4

Single-synapse analyses of Alzheimers disease implicate pathologic tau, DJ1, CD47, and ApoE [article]

Thanaphong Phongpreecha, Chandresh R. Gajera, Candace C. Liu, Kausalia Vijayaragavan, Alan L. Chang, Martin Becker, Ramin Fallahzadeh, Rosemary Fernandez, Nadia Postupna, Emily Sherfield, Dmitry Tebaykin, Caitlin Latimer (+11 others)
2021 bioRxiv   pre-print
We used mass cytometry to quantify 38 probes in approximately 17 million single synaptic events from human brains without pathologic change or with pure AD or Lewy body disease (LBD), non-human primates  ...  Synaptic molecular characterization is limited for Alzheimers disease (AD).  ...  Figure 2B also visualizes select subpopulations, such as BA9's A1, B1, and C4, by density plots of a 2-step gating strategy optimized by GateFinder (29) .  ... 
doi:10.1101/2021.06.14.448240 fatcat:pp5nvq72sjb2dbzzqw7wl5bxya