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 Experiment Videos

Normality of oligonucleotide microarray data and implications for parametric statistical analyses.

Peter J Giles1, David Kipling

  • 1Department of Pathology, University of Wales College of Medicine, Heath Park, Cardiff CF14 4XN, UK.

Bioinformatics (Oxford, England)
|November 25, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Human primary antibody response to vaccination follows a partially sequential class-switching program with a checkpoint at IGHG2.

Cell reports. Medicine·2026
Same author

Diversification of immunoglobulin genes by gene conversion in the domestic chicken (<i>Gallus gallus</i> domesticus).

Discovery immunology·2024
Same author

Role of Enzymic Antioxidants in Mediating Oxidative Stress and Contrasting Wound Healing Capabilities in Oral Mucosal/Skin Fibroblasts and Tissues.

Antioxidants (Basel, Switzerland)·2023
Same author

B cell profiles, antibody repertoire and reactivity reveal dysregulated responses with autoimmune features in melanoma.

Nature communications·2023
Same author

Pandemic, Epidemic, Endemic: B Cell Repertoire Analysis Reveals Unique Anti-Viral Responses to SARS-CoV-2, Ebola and Respiratory Syncytial Virus.

Frontiers in immunology·2022
Same author

Novel pyrrolobenzodiazepine benzofused hybrid molecules inhibit NF-κB activity and synergise with bortezomib and ibrutinib in hematological cancers.

Haematologica·2020
Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·2026
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
See all related articles

Parametric tests are suitable for analyzing Affymetrix GeneChip data, even for low-expressed genes. This study confirms that expression values generally follow a normal distribution, supporting the use of these statistical methods without data transformation.

Area of Science:

  • Bioinformatics
  • Statistical Genetics
  • Genomics

Background:

  • Parametric statistical tests are widely used for identifying differentially regulated genes in microarray data.
  • These tests rely on the assumption of normally distributed data, which has not been thoroughly evaluated for Affymetrix GeneChip data.
  • Previous experimental limitations have driven the popularity of parametric tests.

Purpose of the Study:

  • To critically assess the normality assumption of replicate expression values in Affymetrix GeneChip data.
  • To investigate the distribution of gene expression data generated by different software packages.

Main Methods:

  • Utilized a dataset of 59 human Affymetrix U95A GeneChips with identical target RNA.
  • Employed a combination of statistical tests and visualization techniques to analyze expression values.

Related Experiment Videos

  • Evaluated data processed by four different commercial and academic software packages.

    • Main Results:

    • The majority of probe sets across most analysis suites exhibited expression data well-correlated with normality.
    • A significant number of low-expressed genes in data processed by Affymetrix Microarray Suite 5.0 showed a striking non-normal distribution.
    • Overall, expression data demonstrated good adherence to normality.

    Conclusions:

    • The findings support the application of parametric statistical tests to Affymetrix GeneChip datasets.
    • Data transformation is generally not required for analyzing GeneChip data using parametric tests.
    • Care should be taken when analyzing low-expressed genes from certain software packages like Affymetrix Microarray Suite 5.0.