A computational framework to emulate the human perspective in flow cytometric data analysis.

PloS One
Surajit Ray, Saumyadipta Pyne

Abstract

In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation. To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Fi...Continue Reading

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Citations

Jul 29, 2016·BMC Bioinformatics·Ariful AzadAlex Pothen
Jul 31, 2021·Cytometry. Part a : the Journal of the International Society for Analytical Cytology·Rita FolcarelliOscar F van den Brink

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Methods Mentioned

BETA
flow cytometry
feature extraction

Software Mentioned

GenePattern package
BioConductor
flowCore
flowScape
CompControl
flowTrans
DTG
. DTG
ODT
. ODT

Related Concepts

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