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

Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma.

Ilhem Diboun1, Lorenz Wernisch, Christine Anne Orengo

  • 1Bioinformatics Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK. idiboun@biochem.ucl.ac.uk

BMC Genomics
|October 13, 2006
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

Effects of Phenytoin on the Retinal Ganglion Cell-Inner Plexiform Layer in Acute Optic Neuritis: Analysis of a Phase II Randomized Trial.

Neurology·2025
Same author

Short-interval intracortical inhibition (SICI): effect of target tracking on variability of responses for 1 mV and 200µV test-alone targets.

Neurophysiologie clinique = Clinical neurophysiology·2025
Same author

Short-interval intracortical inhibition and facilitation in amyotrophic lateral sclerosis related to disease phenotype.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2025
Same author

Variability of the Penn upper motor neuron score in amyotrophic lateral sclerosis: need for a revised score.

Journal of neurology·2025
Same author

Bioinspired adaptable multiplanar mechano-vibrotactile haptic system.

Nature communications·2024
Same author

Threshold tracking transcranial magnetic stimulation and neurofilament light chain as diagnostic aids in ALS.

Annals of clinical and translational neurology·2024
Same journal

Multi-omics analysis identifies loci associated with pyrethroid resistance across sister species in the Anopheles gambiae species complex.

BMC genomics·2026
Same journal

Comparative and population genomics analyses of eared pheasants inhabiting highly varying altitudes.

BMC genomics·2026
Same journal

Identification of differentially expressed lncRNAs in different daily weight gains of Jiangquan black pigs and functional analysis of LOC100518120.

BMC genomics·2026
Same journal

A self-attention-based deep learning model for identifying key genes in insect pupal metamorphosis.

BMC genomics·2026
Same journal

Multiple genomic approaches reveal geographic structure and local selection signals in invasive Anopheles stephensi from the Horn of Africa and Yemen.

BMC genomics·2026
Same journal

Integration of bulk RNA-seq and scRNA-seq reveals cell subsets and gene signatures associated with Glaesserella parasuis infection.

BMC genomics·2026
See all related articles

RNA amplification for gene expression profiling can distort target abundance, potentially masking biological variation. Statistical analysis using limma on amplified samples is most reliable for detecting large gene expression differences.

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • RNA amplification is crucial for gene expression profiling from limited tissue samples.
  • T7-based amplification methods are reproducible but may alter target abundance.
  • The impact of amplification-induced distortions on detecting biological variation requires further investigation.

Purpose of the Study:

  • To evaluate the consequences of RNA amplification on detecting biological variation in gene expression.
  • To assess the usability and limitations of T7-based amplification techniques in microarray analysis.

Main Methods:

  • Utilized the Affymetrix small sample protocol version 2 for RNA amplification.
  • Performed comparative analysis of gene expression ratios between amplified and unamplified samples.

Related Experiment Videos

  • Employed limma and Z-scores statistics for differential gene expression analysis.

    • Main Results:

    • Amplification can distort expression ratios due to scanner dynamic range limitations, often reducing statistical significance.
    • Distortions are more critical for subtle expression differences, impacting the detection of moderate ratios.
    • Limma statistics demonstrated better concordance for significant genes between amplified and unamplified samples compared to Z-scores.

    Conclusions:

    • Microarray analysis of amplified samples is best suited for detecting substantial gene expression differences.
    • The use of limma statistics enhances the reliability of detecting significant gene expression changes in amplified samples.