RT Journal Article SR Electronic T1 Integrated cytometry with machine learning applied to high-content imaging of human kidney tissue for in-situ cell classification and neighborhood analysis JF bioRxiv FD Cold Spring Harbor Laboratory SP 2021.12.27.474025 DO 10.1101/2021.12.27.474025 A1 Seth Winfree A1 Andrew T. McNutt A1 Suraj Khochare A1 Tyler J. Borgard A1 Daria Barwinska A1 Angela R. Sabo A1 Michael J. Ferkowicz A1 James C. Williams, Jr A1 James E. Lingeman A1 Connor J Gulbronson A1 Katherine J. Kelly A1 Timothy A. Sutton A1 Pierre C. Dagher A1 Michael T. Eadon A1 Kenneth W. Dunn A1 Tarek M. El-Achkar YR 2022 UL http://biorxiv.org/content/early/2022/06/21/2021.12.27.474025.abstract AB The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities such as mesoscale and highly multiplexed fluorescence microscopy are increasingly applied to human kidney tissue to create single cell resolution datasets that are both spatially large and multi-dimensional. These single cell resolution high-content imaging datasets have a great potential to uncover the complex spatial organization and cellular make-up of the human kidney. Tissue cytometry is a novel approach used for quantitative analysis of imaging data, but the scale and complexity of such datasets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA’s integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses for hyperdimensional large-scale imaging datasets. These novel capabilities enable the analysis of mesoscale two and three-dimensional multiplexed human kidney imaging datasets (such as CODEX and 3D confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney based on labels, spatial association and their microenvironment or neighborhood membership. VTEA provides integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complement other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.Competing Interest StatementThe authors have declared no competing interest.