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J. Pers. Med. 2016, 6(1), 12; doi:10.3390/jpm6010012

Bioinformatics Workflow for Clinical Whole Genome Sequencing at Partners HealthCare Personalized Medicine

1
Personalized Medicine, Partners HealthCare, Cambridge, MA 02139, USA
2
Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
3
Department of Medicine, Harvard Medical School, Boston, MA 02138, USA
4
Department of Pathology, Harvard Medical School, Boston, MA 02138, USA
5
Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Scott T. Weiss and Stephen B. Liggett
Received: 21 October 2015 / Revised: 27 January 2016 / Accepted: 18 February 2016 / Published: 27 February 2016
(This article belongs to the Special Issue Implementing Personalized Medicine in a Large Health Care System)
View Full-Text   |   Download PDF [637 KB, uploaded 27 February 2016]   |  

Abstract

Effective implementation of precision medicine will be enhanced by a thorough understanding of each patient’s genetic composition to better treat his or her presenting symptoms or mitigate the onset of disease. This ideally includes the sequence information of a complete genome for each individual. At Partners HealthCare Personalized Medicine, we have developed a clinical process for whole genome sequencing (WGS) with application in both healthy individuals and those with disease. In this manuscript, we will describe our bioinformatics strategy to efficiently process and deliver genomic data to geneticists for clinical interpretation. We describe the handling of data from FASTQ to the final variant list for clinical review for the final report. We will also discuss our methodology for validating this workflow and the cost implications of running WGS. View Full-Text
Keywords: clinical sequencing; WGS; NGS; next generation sequencing; bioinformatics; validation; precision medicine clinical sequencing; WGS; NGS; next generation sequencing; bioinformatics; validation; precision medicine
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Tsai, E.A.; Shakbatyan, R.; Evans, J.; Rossetti, P.; Graham, C.; Sharma, H.; Lin, C.-F.; Lebo, M.S. Bioinformatics Workflow for Clinical Whole Genome Sequencing at Partners HealthCare Personalized Medicine. J. Pers. Med. 2016, 6, 12.

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