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Updated: Jul 26, 2025

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Published on: March 14, 2022

RETROFIT: Reference-free deconvolution of cell-type mixtures in spatial transcriptomics.

Roopali Singh¹, Xi He¹, Adam Keebum Park¹

¹The Pennsylvania State University, University Park, PA 16802.

Biorxiv : the Preprint Server for Biology

|June 19, 2023

Summary

This summary is machine-generated.

RETROFIT is a new method that identifies cell types in spatial transcriptomics data without needing separate single-cell data. This reference-free approach accurately reveals cell composition and gene expression patterns in tissues.

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Last Updated: Jul 26, 2025

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

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Published on: March 14, 2022

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

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Published on: May 22, 2017

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Area of Science:

Computational Biology
Genomics
Bioinformatics

Background:

Spatial transcriptomics (ST) enables gene expression profiling within intact tissues.
ST data often contains mixed cell types per location, complicating cell-type-specific analysis.
Current deconvolution methods rely on single-cell references, which have limitations.

Conclusions:

RETROFIT provides a robust and independent approach for analyzing spatial transcriptomics data.
The method enhances the understanding of cellular heterogeneity and spatial organization in tissues.
RETROFIT is publicly available, facilitating broader application in biological research.