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

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

You might also read

Related Articles

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

Sort by

Same author

The PRECISE European initiative for cancer-vulnerability mapping and prediction.

Nature genetics·2026

Same author

Impact of vitamin D on the colon cancer immune microenvironment: results of a randomized clinical trial of preoperative vitamin D supplementation in patients with stage I-III colon cancer.

Cancer discovery·2026

Same author

Spatiotemporal dynamics of adoptively transferred stem-like CD8<sup>+</sup> T cells in the tumor microenvironment following vaccination.

bioRxiv : the preprint server for biology·2026

Same author

Gemcitabine and nab-paclitaxel with or without the VDR agonist paricalcitol for metastatic pancreatic cancer: a randomized, multiarm, run-in phase trial.

Nature cancer·2026

Same author

Genome instability triggers intercellular DNA transfer between human cells.

Cell·2026

Same author

Pan-cancer analysis in the real-world setting uncovers immunogenomic drivers of acquired resistance post-immunotherapy.

Journal for immunotherapy of cancer·2026

Search research articles

Related Experiment Video

Updated: May 23, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

scAI-SNP: a method for inferring ancestry from single-cell data.

Sung Chul Hong¹, Francesc Muyas², Isidro Cortés-Ciriano²

¹Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215 USA.

|May 22, 2025

Summary

We developed scAI-SNP, a tool to infer donor ancestry from single-cell genomics data. This method ensures single-cell atlases represent human genetic diversity for equitable health outcomes.

Keywords:

Ancestry SNP Single-cell transcriptomics The 1000 Genomes Project scAI-SNP

More Related Videos

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

Author Spotlight: Vascular Tissue Dissociation and Exploring Single-Cell Subclusters for Targeted Therapy

Author Spotlight: Vascular Tissue Dissociation and Exploring Single-Cell Subclusters for Targeted Therapy

Published on: January 19, 2024

Related Experiment Videos

Last Updated: May 23, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

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

Author Spotlight: Vascular Tissue Dissociation and Exploring Single-Cell Subclusters for Targeted Therapy

Author Spotlight: Vascular Tissue Dissociation and Exploring Single-Cell Subclusters for Targeted Therapy

Published on: January 19, 2024

Area of Science:

Genomics
Population Genetics
Bioinformatics

Background:

Large-scale single-cell data initiatives like the Human Cell Atlas require accurate donor ancestry information.
Self-reported race and ethnicity can be biased and unavailable for existing datasets.

Purpose of the Study:

To introduce scAI-SNP, a novel computational tool for inferring donor ancestry directly from single-cell genomics data.
To address the need for representative single-cell atlases reflecting human genetic diversity.

Main Methods:

Trained scAI-SNP using 4.5 million ancestry-informative single-nucleotide polymorphisms (SNPs) from the 1000 Genomes Project dataset (3201 individuals, 26 populations).
scAI-SNP computes the contribution of 26 population groups to a donor's ancestry from query single-cell data.

Main Results:

scAI-SNP accurately infers ancestry from sparse single-cell data across diverse tissues and cell types (including cancer).
The tool is robust and applicable to various single-cell profiling modalities like scRNA-seq and scATAC-seq.
Demonstrated consistency in ancestry inference using matched whole-genome sequencing data.

Conclusions:

Ensuring diverse ancestry representation in single-cell atlases is crucial for equitable health outcomes.
scAI-SNP provides a robust method to determine ancestry from single-cell genomics data.
Integrating ancestry information alongside race and ethnicity is vital for understanding and addressing human diversity in health.