Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Cancers Originate from Somatic Mutations in a Single Cell

Cancers Originate from Somatic Mutations in a Single Cell

Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Unraveling the role of lactylation in cell death and correlative diseases: a comprehensive review.

Frontiers in cell and developmental biology·2026

Same author

HNRNPA0 Acts as a Master Upstream Regulator of NF-κB to Drive Oncogenic Phenotypes in Oral Squamous Cell Carcinoma.

International dental journal·2026

Same author

Impact of ΔF508 CFTR Mutation on Diaphragm Function During Acute Inflammation.

American journal of physiology. Cell physiology·2026

Same author

Environmental regulation of seed germination and emergence in two populations of Cyperus rotundus L. (Cyperaceae), a weed species with industrial potential.

BMC plant biology·2026

Same author

TRUST: A toolkit for TEE-assisted secure outsourced computation over integers.

Fundamental research·2026

Same author

Uncovering the Key Circuit FOSL2/FOS/EGR3/EGR1, Contributing to the Hyperexcitability of Excitatory Neurons in the Epileptic Temporal Cortex and Hippocampus.

International journal of molecular sciences·2026

Search research articles

Related Experiment Video

Updated: Jan 17, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Computational tracking of cell origins using CellSexID from single-cell transcriptomes.

Huilin Tai¹, Qian Li², Jingtao Wang³

¹Meakins-Christie Laboratories, Research Institute of McGill University Health Centre, 1001 Decarie Boulevard, Montreal, QC H4A 3J1, Canada; Department of Mathematics and Statistics, McGill University, 845 Sherbrooke Street West, Montreal, QC H3A 0G4, Canada; Department of Computer Science, Columbia University, New York, NY, USA.

Cell Reports Methods

|September 18, 2025

Summary

CellSexID uses sex as a marker to track cells in mixed populations. This computational tool accurately distinguishes donor from recipient cells, offering a practical alternative to physical labeling in research.

Keywords:

CP: systems biology cell-origin tracking chimeric models demultiplexing machine learning organ transplantation sex prediction single cell

More Related Videos

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

Related Experiment Videos

Last Updated: Jan 17, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

Area of Science:

Developmental Biology
Regenerative Medicine
Transplantation Research

Background:

Cell tracking in chimeric models is crucial but challenging.
Existing methods like fluorescent labeling are costly and complex.
Dynamic tissues require innovative cell tracking solutions.

Purpose of the Study:

To introduce CellSexID, a computational framework for inferring cell origin.
To utilize sex as a surrogate marker for distinguishing cell populations.
To provide a practical alternative to physical cell labeling.

Main Methods:

Machine learning models trained on single-cell transcriptomic data.
Ensemble feature selection to identify minimal sex-linked gene sets.
Validation using public datasets and experimental flow sorting.

Main Results:

CellSexID accurately predicts individual cell sex.
Enables in silico distinction of donor and recipient cells in sex-mismatched settings.
Demonstrated applicability in chimeric models, organ transplantation, and sample demultiplexing.

Conclusions:

CellSexID offers a cost-effective and practical approach to cell tracking.
Facilitates precise cell tracking in diverse biomedical applications.
Supports the distinction of mixed cellular populations without physical labeling.