alexa Massively parallel sequencing: the next big thing in genetic medicine.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Data Mining in Genomics & Proteomics

Author(s): Tucker T, Marra M, Friedman JM

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Abstract Massively parallel sequencing has reduced the cost and increased the throughput of genomic sequencing by more than three orders of magnitude, and it seems likely that costs will fall and throughput improve even more in the next few years. Clinical use of massively parallel sequencing will provide a way to identify the cause of many diseases of unknown etiology through simultaneous screening of thousands of loci for pathogenic mutations and by sequencing biological specimens for the genomic signatures of novel infectious agents. In addition to providing these entirely new diagnostic capabilities, massively parallel sequencing may also replace arrays and Sanger sequencing in clinical applications where they are currently being used. Routine clinical use of massively parallel sequencing will require higher accuracy, better ways to select genomic subsets of interest, and improvements in the functionality, speed, and ease of use of data analysis software. In addition, substantial enhancements in laboratory computer infrastructure, data storage, and data transfer capacity will be needed to handle the extremely large data sets produced. Clinicians and laboratory personnel will require training to use the sequence data effectively, and appropriate methods will need to be developed to deal with the incidental discovery of pathogenic mutations and variants of uncertain clinical significance. Massively parallel sequencing has the potential to transform the practice of medical genetics and related fields, but the vast amount of personal genomic data produced will increase the responsibility of geneticists to ensure that the information obtained is used in a medically and socially responsible manner.
This article was published in Am J Hum Genet and referenced in Journal of Data Mining in Genomics & Proteomics

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