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Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data

Using an Illumina exome sequencing dataset generated from pediatric Acute Myeloid Leukemia patients (AML; type FLT3/ITD+) a comprehensive bioinformatics pipeline was developed to aid in a better clinical understanding of the genetic data associated with the clinical phenotype. The pipeline starts wi...

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Autores principales: Crowgey, Erin L., Kolb, Anders, Wu, Cathy H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525226/
https://www.ncbi.nlm.nih.gov/pubmed/26306272
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author Crowgey, Erin L.
Kolb, Anders
Wu, Cathy H.
author_facet Crowgey, Erin L.
Kolb, Anders
Wu, Cathy H.
author_sort Crowgey, Erin L.
collection PubMed
description Using an Illumina exome sequencing dataset generated from pediatric Acute Myeloid Leukemia patients (AML; type FLT3/ITD+) a comprehensive bioinformatics pipeline was developed to aid in a better clinical understanding of the genetic data associated with the clinical phenotype. The pipeline starts with raw next generation sequencing reads and using both publicly available resources and custom scripts, analyzes the genomic data for variants associated with pediatric AML. By incorporating functional information such as Gene Ontology annotation and protein-protein interactions, the methodology prioritizes genomic variants and returns disease specific results and knowledge maps. Furthermore, it compares the somatic mutations at diagnosis with the somatic mutations at relapse and outputs variants and functional annotations that are specific for the relapse state.
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spelling pubmed-45252262015-08-24 Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data Crowgey, Erin L. Kolb, Anders Wu, Cathy H. AMIA Jt Summits Transl Sci Proc Articles Using an Illumina exome sequencing dataset generated from pediatric Acute Myeloid Leukemia patients (AML; type FLT3/ITD+) a comprehensive bioinformatics pipeline was developed to aid in a better clinical understanding of the genetic data associated with the clinical phenotype. The pipeline starts with raw next generation sequencing reads and using both publicly available resources and custom scripts, analyzes the genomic data for variants associated with pediatric AML. By incorporating functional information such as Gene Ontology annotation and protein-protein interactions, the methodology prioritizes genomic variants and returns disease specific results and knowledge maps. Furthermore, it compares the somatic mutations at diagnosis with the somatic mutations at relapse and outputs variants and functional annotations that are specific for the relapse state. American Medical Informatics Association 2015-03-23 /pmc/articles/PMC4525226/ /pubmed/26306272 Text en ©2015 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Crowgey, Erin L.
Kolb, Anders
Wu, Cathy H.
Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data
title Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data
title_full Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data
title_fullStr Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data
title_full_unstemmed Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data
title_short Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data
title_sort development of bioinformatics pipeline for analyzing clinical pediatric ngs data
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525226/
https://www.ncbi.nlm.nih.gov/pubmed/26306272
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