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

Comparing three methods for variance estimation with duplicated high density oligonucleotide arrays.

Xiaohong Huang1, Wei Pan

  • 1Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis 55455-0378, USA.

Functional & Integrative Genomics
|August 20, 2002
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

Identification of the miRNA-mRNA regulatory network in multiple sclerosis.

Neurological research·2016
Same author

Long non-coding RNA PVT1 promotes osteosarcoma development by acting as a molecular sponge to regulate miR-195.

Oncotarget·2016
Same author

Fluorescent Nanocomposite for Visualizing Cross-Talk between MicroRNA-21 and Hydrogen Peroxide in Ischemia-Reperfusion Injury in Live Cells and In Vivo.

Analytical chemistry·2016
Same author

Propensity Score Methods in Nursing Research: Take Advantage of Them but Proceed With Caution.

Nursing research·2016
Same author

Optical Fiber Temperature and Torsion Sensor Based on Lyot-Sagnac Interferometer.

Sensors (Basel, Switzerland)·2016
Same author

Silica dioxide nanoparticles combined with cold exposure induce stronger systemic inflammatory response.

Environmental science and pollution research international·2016

Accurate variance estimation is crucial for identifying differentially expressed genes in microarray experiments. Smoothed sample variance offers a reliable and generalizable method, especially with limited replicated data.

Area of Science:

  • Molecular Biology
  • Biostatistics
  • Bioinformatics

Background:

  • Microarray experiments are vital for analyzing gene expression across different conditions.
  • Accurate variance estimation is essential for statistical methods like the t-statistic in differential gene expression analysis.
  • Estimating variance can be challenging with a small number of replicated microarray experiments.

Purpose of the Study:

  • To compare the performance of three statistical methods for variance estimation in microarray experiments.
  • To evaluate the impact of different variance estimation methods on t-statistics.
  • To recommend a suitable method for variance estimation with limited replicates.

Main Methods:

  • Comparison of three variance estimation approaches: simple averaging, and two nonparametric smoothing methods.

Related Experiment Videos

  • Application of methods to a colon cancer dataset with 2,000 genes and two arrays.
  • Empirical assessment of variance estimates and their effect on t-statistics.

    • Main Results:

    • The three compared methods yielded similar variance estimates.
    • All methods were applied to a colon cancer dataset.
    • The smoothed sample variance is recommended for its simplicity and generality.

    Conclusions:

    • Smoothed sample variance is a robust and generally applicable method for variance estimation in microarray studies with few replicates.
    • The choice of variance estimation method had a notable impact on t-statistics.
    • Further research should explore the performance of these methods in diverse biological contexts.