Difference between revisions of "Template:Article of the week"

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(Updated article of the week text.)
(Updated article of the week text.)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig5 Ye JofPathInformatics2016 7.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Tsai JofPersMed2016 6-1.png|80px]]</div>
'''"[[Journal:Pathology report data extraction from relational database using R, with extraction from reports on melanoma of skin as an example|Pathology report data extraction from relational database using R, with extraction from reports on melanoma of skin as an example]]"'''
'''"[[Journal:Bioinformatics workflow for clinical whole genome sequencing at Partners HealthCare Personalized Medicine|Bioinformatics workflow for clinical whole genome sequencing at Partners HealthCare Personalized Medicine]]"'''


The olog approach of Spivak and Kent is applied to the practical development of data transfer frameworks, yielding simple rules for construction and assessment of data transfer standards. The simplicity, extensibility and modularity of such descriptions allows discipline experts unfamiliar with complex ontological constructs or toolsets to synthesize multiple pre-existing standards, potentially including a variety of file formats, into a single overarching ontology. These ontologies nevertheless capture all scientifically-relevant prior knowledge, and when expressed in machine-readable form are sufficiently expressive to mediate translation between legacy and modern data formats. A format-independent programming interface informed by this ontology consists of six functions, of which only two handle data. Demonstration software implementing this interface is used to translate between two common diffraction image formats using such an ontology in place of an intermediate format. ('''[[Journal:Pathology report data extraction from relational database using R, with extraction from reports on melanoma of skin as an example|Full article...]]''')<br />
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 [[Genomics|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. ('''[[Journal:Bioinformatics workflow for clinical whole genome sequencing at Partners HealthCare Personalized Medicine|Full article...]]''')<br />
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''Recently featured'':  
''Recently featured'':  
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Revision as of 17:27, 30 January 2017

Fig2 Tsai JofPersMed2016 6-1.png

"Bioinformatics workflow for clinical whole genome sequencing at Partners HealthCare Personalized Medicine"

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. (Full article...)

Recently featured:

Pathology report data extraction from relational database using R, with extraction from reports on melanoma of skin as an example
A robust, format-agnostic scientific data transfer framework
A benchmarking analysis of open-source business intelligence tools in healthcare environments