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Researchers build SEQSpark to analyze massive genetic data sets

02:22 EDT 30 Jun 2017 | Medical Xpress

Uncovering rare susceptibility variants that contribute to the causes of complex diseases requires large sample sizes and massively parallel sequencing technologies. These sample sizes, often made up of exome and genome data from tens to hundreds of thousands of individuals, are often too large for current analytical tools to process. A team at Baylor College of Medicine, led by Dr. Suzanne Leal, professor of molecular and human genetics, has developed new software called SEQSpark to overcome this processing obstacle. A study on the new technology appears in The American Journal of Human Genetics.

Original Article: Researchers build SEQSpark to analyze massive genetic data sets

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