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Mistic: An Open-Source Multiplexed Image t-SNE Viewer

12 Pages Posted: 2 Dec 2021 Publication Status: Published

See all articles by Sandhya Prabhakaran

Sandhya Prabhakaran

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology

Chandler D. Gatenbee

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology

Mark Robertson-Tessi

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology

Jeffrey West

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology

Amer Beg

H. Lee Moffitt Cancer Center and Research Institute - Department of Immunology

Jhanelle Gray

H. Lee Moffitt Cancer Center and Research Institute - Department of Immunology

Scott Antonia

Duke University - Department of Medicine

Robert A. Gatenby

H. Lee Moffitt Cancer Center and Research Institute - Department of Radiation Oncology

Alexander R.A. Anderson

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology

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Abstract

Understanding the complex ecology of a tumor tissue and the spatio-temporal relationships between its cellular and microenvironment components is becoming a key component of translational research, especially in immune-oncology. The generation and analysis of multiplexed images from patient samples is of paramount importance to facilitate this understanding. In this work, we present Mistic, an open-source multiplexed image t-SNE viewer that enables the simultaneous viewing of multiple 2D images rendered using multiple layout options to provide an overall visual preview of the entire dataset. In particular, the positions of the images can be taken from t-SNE or UMAP coordinates. This grouped view of all the images further aids an exploratory understanding of the specific expression pattern of a given biomarker or collection of biomarkers across all images, helps to identify images expressing a particular phenotype or to select images for subsequent downstream analysis. Currently there is no freely available tool to generate such image t-SNEs. Mistic is open-source and can be downloaded at: https://github.com/MathOnco/Mistic.

Keywords: Multiplexed images, Visualization, Dimensionality reduction, NSCLC, Data analysis, tSNE, UMAP, software

Suggested Citation

Prabhakaran, Sandhya and Gatenbee, Chandler D. and Robertson-Tessi, Mark and West, Jeffrey and Beg, Amer and Gray, Jhanelle and Antonia, Scott and Gatenby, Robert A. and Anderson, Alexander R.A., Mistic: An Open-Source Multiplexed Image t-SNE Viewer. Available at SSRN: https://ssrn.com/abstract=3976483 or http://dx.doi.org/10.2139/ssrn.3976483
This version of the paper has not been formally peer reviewed.

Sandhya Prabhakaran

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology ( email )

United States

Chandler D. Gatenbee

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology ( email )

United States

Mark Robertson-Tessi

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology ( email )

United States

Jeffrey West

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology ( email )

United States

Amer Beg

H. Lee Moffitt Cancer Center and Research Institute - Department of Immunology ( email )

Tampa, FL
United States

Jhanelle Gray

H. Lee Moffitt Cancer Center and Research Institute - Department of Immunology ( email )

Tampa, FL
United States

Scott Antonia

Duke University - Department of Medicine ( email )

Durham, NC 27710
United States

Robert A. Gatenby

H. Lee Moffitt Cancer Center and Research Institute - Department of Radiation Oncology ( email )

Tampa, FL
United States

Alexander R.A. Anderson (Contact Author)

H. Lee Moffitt Cancer Center and Research Institute - Department of Integrated Mathematical Oncology ( email )

United States

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