Best Practices in Genetic Analysis - Page 6 of 6

Public Data? What’s that good for anyway?

Dr. Bryce Christensen recently gave a webcast on Maximizing Public Data Sources for Sequencing and GWAS Studies in which he covered options for getting GWAS and sequence information online, tips for working with these datasets and what you’ll see in terms of data quality and usefulness, how to use public…

Guest Post: Finding Rare Pieces of Hay in a Haystack

Utilizing Identical Twins Discordant for Schizophrenia to Uncover de novo Mutations We are living in exciting times – the reality of high-resolution Cand individual genome sequencing now offers renewed hope in the search for the causes of complex diseases. When this technology is combined with genetic relationships, individual sequences add…

Population Structure + Genetic Background + Environment = Mixed Model

A few months ago, our CEO, Christophe Lambert, directed me toward an interesting commentary published in Nature Reviews Genetics by authors Bjarni J. Vilhjalmsson and Magnus Nordborg. Population structure is frequently cited as a major source of confounding in GWAS, but the authors of the article suggest that the problems…

Follow Along on an Analyst’s Journey to Filter Whole Genome Data to Four Candidate Variants in SVS

Last week Khanh-Nhat Tran-Viet, Manager/Research Analyst II at Duke University, presented the webcast: Insights: Identification of Candidate Variants using Exome Data in Ophthalmic Genetics. (That link has the recording if you are interested in viewing.) In it, Khanh-Nhat highlighted tools available in SVS that might be under used or were…

A Conversation with 1000 Genomes Analysis Group Member: Jeffrey Rosenfeld

After my latest blog post, Jeffrey Rosenfeld reached out to me. Jeff is a member of the Analysis Group of the 1000 Genomes Project and shared some fascinating insights that I got permission to share here: Hi Gabe, I saw your great blog post about the problems in the lack…

Dr. Ken Kaufman’s Webcast on Exome Sequencing Wildly Successful

Thank you to everyone who joined us yesterday for a webcast by Dr. Ken Kaufman of Cincinnati Children’s Hospital: “Identification of Candidate Functional Polymorphism Using Trio Family Whole Exome DNA Data.” Over 750 people registered for this event and 430 attended – a new Golden Helix record! If you missed…

Why You Should Care About Segmental Duplications

My work in the GHI analytical services department gives me the opportunity to handle data from a variety of sources. I have learned over time that every genotyping platform has its own personality. Every time we get data from a new chip, I tend to learn something new about the…

Best Practices for Incorporating Public Genotype Data in Your Study

The Golden Helix sales team recently came to me for recommendations regarding best practices for incorporating public controls in SNP GWAS. It seems that there has been a surge of questions regarding this practice over the past few weeks from our customers. Initially, I laughed at the irony of being…

Stop Ignoring Experimental Design (or my head will explode)

Stop Ignoring Experimental Design (or my head will explode)

Over the past 3 years, Golden Helix has analyzed dozens of public and customer whole-genome and candidate gene datasets for a host of studies. Though genetic research certainly has a number of complexities and challenges, the number one problem we encounter, which also has the greatest repercussions, is born of…

Enhanced ROH Analysis Improves Effectiveness to Identify Rare, Penetrant Recessive Loci

In the paper Runs of homozygosity reveal highly penetrant recessive loci in schizophrenia, Todd Lencz, Ph.D. introduced a new way of doing association testing using SNP microarray platforms. The method, which he termed “whole genome homozygosity association”, first identifies patterned clusters of SNPs demonstrating extended homozygosity (runs of homozygosity or…