We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us

Download Mobile App




New Computational Approach Helps Genomic Researchers Pinpoint Disease-Causing Genetic Variants

By LabMedica International staff writers
Posted on 18 Sep 2012
A team of genomic researchers has developed a computer program that enables them to screen the masses of data generated by genome-wide association studies (GWASs) in order to isolate specific gene variants (causal variants) linked to specific diseases.

The computational method, which is called the preferential linkage disequilibrium approach, was developed by molecular biologists and bioinformatics specialists at Duke University (Durham, NC, USA) and their collaborators at the Roswell Park Cancer Institute (Buffalo, NY, USA). More...
The program tracks variants reported by GWASs, then cross-references those of interest against a comprehensive variant catalog generated through robust “next-generation” sequencing in order to pinpoint causal variants.

To confirm the validity of the approach the investigators applied it to the GWAS signals of five human traits for which the causal variants were already known. Results detailed in the August 30, 2012, issue of the American Journal of Human Genetics, revealed that they had successfully placed the known causal variants among the top ten candidates in the majority of the cases. Further application of this method to additional GWASs, including those of hepatitis C virus treatment response, plasma levels of clotting factors, and late-onset Alzheimer's disease, has led to the identification of a number of promising candidate causal variants.

“This approach helps to intergrade the large body of data available in GWASs with the rapidly accumulating sequence data,” said senior author Dr. David B. Goldstein, professor of molecular genetics and microbiology at Duke University.

Related Links:
Duke University
Roswell Park Cancer Institute


Gold Member
Automatic Hematology Analyzer
CF9600
Online QC Software
Acusera 24•7
HPV Test
Allplex HPV28 Detection
HPV Molecular Test
BD Onclarity HPV Assay
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Clinical Chemistry

view channel
Image: Characterization of EV separated by distinct methods (Photo courtesy of Yuanyuan Liu, Yanbin Guo et al. Engineering, doi.org/10.1016/j.eng.2025.12.009)

Liquid Biopsy Biomarkers May Improve Childhood Epilepsy Diagnosis

Childhood epilepsy remains a major neurological disorder with unmet needs for accurate, non-invasive biomarkers, as conventional tests such as electroencephalography and neuroimaging can have limited sensitivity... Read more

Molecular Diagnostics

view channel
Image: Associate Professor Arutha Kulasinghe and non-small cell lung cancer cell (Photo courtesy of The University of Queensland)

Blood-Based Proteomic Test May Predict Treatment Response in Non-Small Cell Lung Cancer

Lung cancer remains the leading cause of cancer death, with non-small cell lung cancer (NSCLC) accounting for most cases. Treatment decisions are often made without a clear indication of how a patient... Read more

Pathology

view channel
Image: Immune-related signals in routine bone marrow biopsy slides could help predict multiple myeloma outcomes and support more personalized treatment strategies (image credit: Shutterstock)

AI Tool Extracts Immune Signals from Biopsy to Inform Myeloma Therapy

Multiple myeloma is a bone marrow malignancy in which patients can respond very differently to the same treatments, making initial therapy decisions difficult. Clinicians must choose among options such... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.