Deerwalk Blog

Big Data Genomics

Posted by Narendra Maden on January 09, 2015

Genetic diseases are caused by faulty DNA (i.e. mutations). They can be single or multigene disorders. At present, over 4000 single gene disorders are known. Gene’s role is being deciphered to more and more diseases. Some of the well-known genetic diseases are diabetes, heart disease, cancer, and Alzheimer’s disease. According to American Cancer Society, in the US alone, a total of 1,658,370 new cancer cases and 589,430 deaths from cancer (a multifactorial disease including genetic component) are projected to occur in 2015. This tells the enormity of the health burden due to genetic diseases. There is no cure for genetic diseases right now, but science is moving in that direction.

Diagnosis, treatment and prevention of genetic disorders are a complex process, which involves the patient, provider and an entire industry of researchers, technicians and data scientists. Patients and providers work together to identify that a whole genome testing is appropriate for a particular diagnosis and a sample is sent to a wet lab. The DNA sample is then evaluated by high throughput next-generation sequencing (NGS). This machine analyzes the all genes (around 24 thousands) in the sample and outputs terabytes of data for analysis.

Genomic research and testing have gone through rapid changes over the past decade since the Human Genome Project completed. Barriers have broken down and technological advances have significantly reduced the price to sequence samples from patients. We believe the cost to sequence will continue to decline over time and the next challenge is how to handle all of the data that is produced from the sequence. Through years of experience in big data healthcare analysis and working with experts in the field, Deerwalk Genomics is perfectly positioned to tackle this problem.

Deerwalk Genomics has been working on ‘dry lab work’ with genetic testing companies for several years. Our team provides end-to-end data solutions for big data genomics including:

  • Interpretation of genetic variants
  • Building genetic variant databases
  • Analytic solutions to Sanger sequencing/re-sequencing
  • Curation of overall information for genetic diseases
  • Building software solutions for risk analysis and predictive modeling

We anticipate exponential growth in the genomics arena as sequencing becomes more common in US healthcare. Our team actively develops the key analytical processes for genome big data to separate disease-relevant mutations from benign changes in the genome. The library of disease-relevant mutations is increasing daily and we harness this cutting-edge research to ensure that our analytical processes best support patient diagnosis and outcomes.BigDataGenomics2-3.jpg

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