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Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data.

Crowgey EL, Kolb A, Wu CH - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Center for Bioinformatics & Computational Biology, University of Delaware, Newark, DE.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Bioinformatics workflow
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f1-2091834: Bioinformatics workflow

Mentions: Six FLT3/ITD positive samples, with varying allelic ratios and cytogenetic markers were analyzed with a custom pipeline (Figure 1). The pipeline consisted of publicly available algorithms, such as bwa and GATK, plus custom scripts. A key aspect of the established methodologies is the modularization of algorithms and scripts, which creates an environment that allows for the dynamic integration with up-dated algorithms and databases.


Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data.

Crowgey EL, Kolb A, Wu CH - AMIA Jt Summits Transl Sci Proc (2015)

Bioinformatics workflow
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525226&req=5

f1-2091834: Bioinformatics workflow
Mentions: Six FLT3/ITD positive samples, with varying allelic ratios and cytogenetic markers were analyzed with a custom pipeline (Figure 1). The pipeline consisted of publicly available algorithms, such as bwa and GATK, plus custom scripts. A key aspect of the established methodologies is the modularization of algorithms and scripts, which creates an environment that allows for the dynamic integration with up-dated algorithms and databases.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Center for Bioinformatics & Computational Biology, University of Delaware, Newark, DE.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus