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Cell Specific Gene Expression

Cell Specific Gene Expression

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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Updated: Jan 7, 2026

Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library

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Trajectory-informed gene feature selection in single-cell analysis with SEEK-VFI.

Rebecca Danning^1,2, Zheng Tracy Ke³, Xihong Lin^3,4

¹Center for Genomic Medicine, Massachusetts General Hospital.

Biorxiv : the Preprint Server for Biology

|December 25, 2025

Summary

This summary is machine-generated.

SEEK-VFI, a machine learning method, identifies key genes for single-cell trajectory inference. It improves understanding of cell development pathways by prioritizing relevant genes over uninformative ones.

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Area of Science:

Computational Biology
Genomics
Machine Learning

Background:

Prioritizing highly-variable genes is crucial for single-cell trajectory inference.
Standard methods struggle to distinguish trajectory-relevant genes from uninformative ones when variability stems from continuous cell development.

Purpose of the Study:

To introduce SEEK-VFI, an ensemble topic-modeling algorithm designed for trajectory inference preprocessing.
To enhance the prioritization of trajectory-relevant genes in single-cell data.

Main Methods:

SEEK-VFI employs an ensemble topic-modeling approach.
The algorithm is specifically designed for preprocessing steps in trajectory inference.

Main Results:

SEEK-VFI outperforms existing gene prioritization methods.
Identified key genes significantly improve trajectory topology reconstruction.
Enhanced visualization and downstream trajectory analyses were observed.

Conclusions:

SEEK-VFI effectively prioritizes trajectory-relevant genes for single-cell trajectory inference.
The method offers improvements in reconstructing, visualizing, and analyzing cell development trajectories.