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

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

You might also read

Related Articles

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

Sort by
Same author

Does Radiation Boost Dose Affect Organ Preservation Rates? A Secondary Analysis of the Organ Preservation in Patients With Rectal Adenocarcinoma Trial.

International journal of radiation oncology, biology, physics·2026
Same author

Phase 2 study of palbociclib plus retifanlimab in patients with advanced dedifferentiated liposarcoma.

Journal for immunotherapy of cancer·2026
Same author

Association of Circulating T Cell and Tumor Microenvironment Profiles with Immune Checkpoint Blockade Outcomes in Sarcoma.

Clinical cancer research : an official journal of the American Association for Cancer Research·2026
Same author

Tumor and Immune Dynamics Following Sequential CDK4/6 and PD-1 Inhibition: Results from a Phase 2 Study in Dedifferentiated Liposarcoma.

Cancer research communications·2025
Same author

Accuracy of Flexible Sigmoidoscopy and MRI in Restaging Rectal Cancer after Neoadjuvant Therapy: A Secondary Analysis of the OPRA Randomized Clinical Trial.

Annals of surgery·2025
Same author

Histologic Subvariants of Retroperitoneal Well-Differentiated Liposarcoma Show Evidence of Clinical and Genomic Progression Toward Dedifferentiated Liposarcoma.

JCO precision oncology·2025

Related Experiment Video

Updated: Jun 25, 2026

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
09:58

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Normalization method for transcriptional studies of heterogeneous samples--simultaneous array normalization and

Li-Xuan Qin1, Jaya M Satagopan

  • 1Memorial Sloan-Kettering Cancer Center. qinl@mskcc.org

Statistical Applications in Genetics and Molecular Biology
|February 19, 2009
PubMed
Summary

This study introduces a new method for normalizing microarray data by simultaneously identifying non-differentially expressed genes. This approach improves transcription profiling analysis, especially when differential gene expression is common or asymmetric.

More Related Videos

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
09:27

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

Related Experiment Videos

Last Updated: Jun 25, 2026

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
09:58

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
09:27

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

Area of Science:

  • Bioinformatics
  • Genomics
  • Statistical Modeling

Background:

  • Microarray data analysis requires normalization to correct for systematic, non-biological variations.
  • Current normalization methods often rely on assumptions about differential gene expression that may not hold true.
  • Identifying non-differentially expressed genes for normalization is challenging as their status is initially unknown.

Purpose of the Study:

  • To propose a novel hierarchical mixture model for simultaneous identification of non-differentially expressed genes and array normalization.
  • To provide a more robust normalization strategy for transcription profiling data.
  • To evaluate the performance of the proposed method against existing techniques.

Main Methods:

  • Development of a hierarchical mixture model framework.
  • Simultaneous identification of non-differentially expressed genes and array normalization.
  • Derivation of the Fisher's information matrix for array effects to guide normalization choices.
  • Evaluation using simulated data across various parametric configurations.

Main Results:

  • The proposed method demonstrates improved sensitivity compared to median normalization, particularly with moderate or asymmetric differential gene expression.
  • It performs comparably to median normalization when the prevalence of differential expression is very low.
  • Simulations indicate the method is a valuable alternative for array normalization.

Conclusions:

  • The hierarchical mixture model offers a robust approach to microarray data normalization by directly addressing the challenge of identifying suitable reference genes.
  • This method enhances the accuracy of transcription profiling analysis, especially in complex biological samples.
  • The approach is validated through simulations and an empirical study on liposarcoma tissues.