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NIGMS to Fund Research into Interpretation of Sequencing Data

NEW YORK (GenomeWeb News) – The National Institute of General Medical Sciences will fund research into new ways of exploring next-generation sequencing data that will be useful in evaluating the functional relevance of individual variants in the human genome.

Under a new funding program, NIGMS plans to provide $3 million in fiscal year 2013 for research project grants funding efforts that use biochemical, cellular, bioinformatic, statistical, and/or high-throughput methods to develop new principles underlying the interpretation of DNA sequence variation in well-phenotyped populations.

These projects may connect human studies to complementary research into model organisms, and they should seek to design or validate creative and efficient experimental and computational approaches to determine the functional relevance of sequence variants in the human genome.

According to NIGMS, there is a shortage of strategies for determining which variations at certain genetic loci are biologically important, and there is a need to define how variations at many loci work together to create a particular phenotype. At the individual level, there are opportunities to integrate genomic information with systems biology and clinical phenotype.

Investigators may use this NIGMS funding for projects that pursue these aims through a range of research topics. They may seek to develop and test functional screens and algorithms that rapidly analyze the impact of a variant on a specific biological function, develop methods to understand how combinations of genetic changes lead to a human trait or heritable disease, or use relevant model organisms to optimize the analysis of which sequence variants lead to a human trait or disease.

They also may use bioinformatics to study existing DNA sequence data to identify variants with biological functions, optimize methods for including ethnic genomic variation in determining whether a sequence variation has functional relevance, or develop statistical models for identifying and characterizing significant variants.

The Scan

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Snipping HIV Out

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PLOS Papers on Cancer Risk Scores, Typhoid Fever in Colombia, Streptococcus Protection

In PLOS this week: application of cancer polygenic risk scores across ancestries, genetic diversity of typhoid fever-causing Salmonella, and more.