Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Stratified Sampling Method01:16

Stratified Sampling Method

13.6K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
13.6K

You might also read

Related Articles

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

Sort by
Same author

Comparison of Robot-Versus Laparoscopy-Assisted Resection of Choledochal Cysts in Infants Aged Less than 3 Months.

Journal of clinical medicine·2026
Same author

TCR-FramePose: a local-frame representation for decomposing global docking and CDR3 loop geometry in TCR-pMHC recognition.

bioRxiv : the preprint server for biology·2026
Same author

A pilot translational study of neoadjuvant fulvestrant plus abemaciclib in women with advanced low-grade serous carcinoma.

Nature communications·2026
Same author

Multi-Strategy Enhanced White Shark Optimizer for Solving Job Shop Scheduling Problem.

Biomimetics (Basel, Switzerland)·2026
Same author

Decoding the Lymphangioleiomyomatosis (LAM) Niche Microenvironment <i>via</i> Integrative Analysis of Single Cell Multiomics and Spatial Transcriptomics.

The European respiratory journal·2026
Same author

Somatic variant detection in normal tissues from single-cell sequencing data.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Oct 29, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

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

Published on: October 25, 2018

6.8K

Stratified Test Accurately Identifies Differentially Expressed Genes Under Batch Effects in Single-Cell Data.

Shaoheng Liang, Qingnan Liang, Rui Chen

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |July 7, 2021
    PubMed
    Summary

    The Van Elteren test, a novel statistical method for single-cell sequencing data, effectively reduces errors in gene expression analysis. This approach enhances accuracy and reliability in large-scale biological studies.

    More Related Videos

    Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
    10:12

    Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

    Published on: January 10, 2019

    18.8K
    Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations
    10:23

    Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

    Published on: January 19, 2017

    11.1K

    Related Experiment Videos

    Last Updated: Oct 29, 2025

    A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
    09:34

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

    Published on: October 25, 2018

    6.8K
    Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
    10:12

    Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

    Published on: January 10, 2019

    18.8K
    Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations
    10:23

    Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

    Published on: January 19, 2017

    11.1K

    Area of Science:

    • Genomics
    • Bioinformatics
    • Statistical analysis

    Background:

    • Analyzing large single-cell sequencing cohorts presents significant challenges.
    • Experimental discrepancies and participant variability introduce false positives and negatives in gene expression analysis.

    Purpose of the Study:

    • To introduce and evaluate the Van Elteren test for analyzing single-cell sequencing data.
    • To improve the accuracy and reliability of differential gene expression analysis in large cohorts.

    Main Methods:

    • The Van Elteren test, a stratified Wilcoxon rank-sum test, was applied.
    • A modified common language effect size was developed to supplement the test.
    • Performance was assessed using simulated and real patient single-cell sequencing data.

    Main Results:

    • The Van Elteren test effectively controls for false positives and false negatives.
    • The modified effect size accurately estimates differences between cell types.
    • Receiver operating characteristic (ROC) curve analysis demonstrated superior sensitivity and specificity compared to nine other methods.

    Conclusions:

    • The Van Elteren test offers a robust solution for analyzing large single-cell sequencing cohorts.
    • This method significantly improves the accuracy of differential gene expression analysis.
    • The enhanced statistical approach aids in more precise biological interpretation.