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

You might also read

Related Articles

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

Sort by
Same author

Multi-omics network inference with a Gaussian copula model.

BMC bioinformatics·2026
Same author

Improving CTV<sub>boost</sub> delineation after preoperative systemic therapy in breast cancer using deformable PET/CT registration.

Breast (Edinburgh, Scotland)·2026
Same author

[Corrigendum to "Indications for total mastectomy with immediate breast reconstruction in oncology: Surgical strategies tailored to breast morphology and adjuvant treatments" [Ann. Chir. Plast. Esth. 70/6 (2025) p. 539-550]].

Annales de chirurgie plastique et esthetique·2026
Same author

CMV seropositivity associates with poor clinical outcome in triple negative breast cancer.

iScience·2026
Same author

SCANDARE: an institutional dynamic prospective interventional biobanking study.

BMC cancer·2026
Same author

Outcomes of Anastrozole, Letrozole, and Exemestane in Patients With Postmenopausal Breast Cancer.

JAMA network open·2026

Related Experiment Video

Updated: Jun 2, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
14:56

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

SMETHILLIUM: spatial normalization method for Illumina infinium HumanMethylation BeadChip.

Camille Sabbah1, Gildas Mazo, Caroline Paccard

  • 1Institut Curie, 26 rue d'Ulm, F-75248, Paris, France.

Bioinformatics (Oxford, England)
|April 16, 2011
PubMed
Summary
This summary is machine-generated.

A new spatial normalization method improves DNA methylation analysis by correcting background noise. This method outperforms existing tools like BeadStudio for accurately predicting methylation states in human cells.

More Related Videos

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
13:47

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
07:50

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

Published on: September 18, 2020

Related Experiment Videos

Last Updated: Jun 2, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
14:56

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
13:47

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
07:50

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

Published on: September 18, 2020

Area of Science:

  • Epigenetics
  • Genomics
  • Bioinformatics

Background:

  • DNA methylation is a critical epigenetic modification in human cells.
  • The Illumina HumanMethylation27 BeadChip enables quantification of methylation at 27,578 loci across 14,495 genes.

Purpose of the Study:

  • To develop a novel non-parametric normalization method for DNA methylation data.
  • To improve the signal-to-noise ratio by correcting spatial background noise.
  • To enhance the prediction accuracy of locus methylation states.

Main Methods:

  • Development of a non-parametric normalization technique.
  • Correction of spatial background noise in methylation data.
  • Assessment of prediction performance using fully methylated and unmethylated DNA samples.

Main Results:

  • The proposed spatial normalization method effectively corrects background noise.
  • The method significantly improves the signal-to-noise ratio of methylation data.
  • Performance evaluation demonstrated superior prediction accuracy compared to BeadStudio.

Conclusions:

  • The developed spatial normalization method is a valuable tool for DNA methylation analysis.
  • This approach enhances the reliability and accuracy of methylation state predictions.
  • The method offers an improvement over existing software for analyzing Illumina HumanMethylation27 BeadChip data.