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You are here: Home / News / 2012 News / Valdar receives $1.4 million grant to leverage collaborative cross

Valdar receives $1.4 million grant to leverage collaborative cross

by maryruth.helms — last modified Oct 15, 2012 09:39 AM
William Valdar, PhD, assistant professor of genetics, has received a 5-year, $1.4 million grant from the National Institute of General Medical Sciences (part of the National Institutes of Health), to develop statistical methods and software to support the design and analysis of experiments that use the Collaborative Cross, a “library” of genetic diversity that scientists believe can help fast-track important discoveries about genetics and disease into new discoveries, tests, and treatments that impact human health.
Valdar receives $1.4 million grant to leverage collaborative cross

Dr. Valdar has received a grant to develop statistical methods and software to support the design and analysis of experiments that use the Collaborative Cross.

Researchers have long been frustrated by promising lab results that hit obstacles on the road to human application.  Sometimes this is because research in other living organisms is very limited in terms of what conclusions scientists can safely extrapolate to the human population as a whole.  One reason for this problem is that organisms studied in the laboratory lack the genetic diversity of humans.

To overcome this obstacle, scientists have begun to create libraries of genetic material.  These libraries – called Genetic Resource Panels (GRPs) – enable researchers to look at how genetic variation impacts living systems in a careful and systematic manner – an approach that they think will help draw more robust conclusions, often more quickly.  The Collaborative Cross, a project aimed at mirroring the diversity of human genetics in the laboratory mouse population, is one such GRP. 

Dr. Valdar will develop statistical methods that both allow scientists to conduct complex trait analysis of genetically diverse populations and a statistical framework that allows for the populations to be compared and contrasted.  The project will generate tools useful for a wide range of GRP models that can be applied to the genetic study of any complex disease.

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