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Cell Specific Gene Expression

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...

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Related Experiment Video

Updated: Jul 30, 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

Celloscope: a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data.

Agnieszka Geras^1,2, Shadi Darvish Shafighi^2,3, Kacper Domżał²

¹Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland.

|May 17, 2023

Summary

This summary is machine-generated.

Celloscope accurately deconvolutes cell types from spatial transcriptomics data. This innovative probabilistic model precisely maps gene expression, revealing tissue architecture and cell composition in complex biological samples.

Keywords:

Cell types MCMC sampling Probabilistic model Spatial transcriptomics data

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Related Experiment Videos

Last Updated: Jul 30, 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

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Published on: January 10, 2019

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:

Genomics
Computational Biology
Bioinformatics

Background:

Spatial transcriptomics enables gene expression mapping within tissues.
A key challenge is deconvoluting mixed cell signals within spatial spots.
Prior knowledge of marker genes is crucial for accurate cell type identification.

Purpose of the Study:

To introduce Celloscope, a novel probabilistic model for cell type deconvolution.
To leverage marker gene information for enhanced spatial transcriptomics analysis.
To validate Celloscope's performance against existing methods and in real biological tissues.

Main Methods:

Development of a probabilistic model (Celloscope).
Integration of prior knowledge on cell type-specific marker genes.
Application to simulated and real spatial transcriptomics datasets (mouse brain, prostate tissue).

Main Results:

Celloscope demonstrated superior performance on simulated data compared to other methods.
Successfully identified known brain structures and distinguished neuron subtypes in mouse brain tissue.
Revealed complex immune cell heterogeneity within prostate gland tissue.

Conclusions:

Celloscope provides a robust framework for cell type deconvolution in spatial transcriptomics.
The model accurately reconstructs tissue architecture and cellular composition.
Enables deeper insights into tissue heterogeneity and cell-cell interactions.