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...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Labeling DNA Probes03:31

Labeling DNA Probes

DNA probes are fragments of DNA labeled with a reporter tag to enable their detection or purification. The resulting labeled DNA probes can then hybridize to target nucleic acid sequences through complementary base-pairing, and may be used to recover or identify these regions.
Radioisotopes, fluorophores, or small molecule binding partners like biotin or digoxigenin, are the most widely used reporter tags for labeling DNA probes. These labels can be attached to the probe DNA molecule via...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

You might also read

Related Articles

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

Sort by
Same author

Next-generation therapeutics and renaissance of legacy drugs targeting the endothelin system.

Canadian journal of physiology and pharmacology·2026
Same author

The first oral relaxin receptor RXFP1 agonist for heart failure treatment: Translational studies from non-human primates to humans.

Molecular therapy. Advances·2026
Same author

Phase 2b trial of an oral relaxin family peptide receptor 1 agonist in patients with chronic heart failure: rationale and design.

ESC heart failure·2026
Same author

Population Pharmacokinetic Analysis of Balcinrenone in Healthy Participants and Participants with Heart Failure and Chronic Kidney Disease.

Clinical pharmacokinetics·2025
Same author

FamLink2 - A comprehensive tool for likelihood computations in pedigrees analyses involving linked DNA markers accounting for genotype uncertainties.

Forensic science international. Genetics·2024
Same author

Effects of Zibotentan Alone and in Combination with Dapagliflozin on Fluid Retention in Patients with CKD.

Journal of the American Society of Nephrology : JASN·2024

Related Experiment Video

Updated: Jul 6, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

Empirical Bayes models for multiple probe type microarrays at the probe level.

Magnus Astrand1, Petter Mostad, Mats Rudemo

  • 1Mathematical Sciences, Chalmers University of Technology, and Mathematical Sciences, Göteborg University, S-41296, Göteborg, Sweden. magnus.astrand@astrazeneca.com

BMC Bioinformatics
|March 28, 2008
PubMed
Summary

Two new methods, Probe level Locally moderated Weighted median-t (PLW) and Locally Moderated Weighted-t (LMW), improve the detection of differentially expressed genes by accounting for intensity-dependent variability in microarray data analysis. These novel approaches offer more accurate gene ranking and robust performance across various data processing methods.

More Related Videos

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs
10:28

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs

Published on: April 14, 2015

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions
08:07

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Published on: August 2, 2015

Related Experiment Videos

Last Updated: Jul 6, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs
10:28

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs

Published on: April 14, 2015

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions
08:07

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Published on: August 2, 2015

Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Microarray data analysis frequently aims to identify differentially expressed genes.
  • Traditional methods like empirical Bayes and penalized t-tests stabilize variance estimates but can yield intensity-dependent false positive rates for Affymetrix data.
  • This intensity-variability dependency is present at both probe and probe-set levels, complicating accurate gene expression analysis.

Purpose of the Study:

  • To develop novel statistical methods for identifying differentially expressed genes that address the intensity-dependent variability in microarray data.
  • To improve the accuracy and reliability of gene expression analysis, particularly for Affymetrix and similar array platforms.

Main Methods:

  • Introduction of Probe level Locally moderated Weighted median-t (PLW) and Locally Moderated Weighted-t (LMW) methods.
  • Both methods employ an empirical Bayes framework to model the relationship between variability and intensity.
  • A global covariance matrix is incorporated to handle inter-array variances and correlations. PLW specifically analyzes individual perfect-match probes before summarizing results for probe-sets.

Main Results:

  • Comparative analysis against 14 existing methods using five spike-in datasets.
  • PLW demonstrated the most accurate gene ranking in four out of five datasets for RMA and GCRMA processed data.
  • LMW consistently outperformed examined moderated t-tests on RMA, GCRMA, and MAS5 expression indexes.

Conclusions:

  • The proposed PLW and LMW methods offer significant improvements in identifying differentially expressed genes.
  • These methods effectively manage intensity-dependent variability, leading to more reliable results in microarray data analysis.
  • PLW and LMW provide robust alternatives for gene expression analysis across different data processing pipelines.