Transcript annotation prioritization and screening system (TrAPSS) for mutation screening

Brian M O'Leary; Steven G Davis; Michael F Smith; Bartley Brown; Mathew B Kemp; Hakeem Almabrazi; Jason A Grundstad; Thomas Burns; Vladimir Leontiev; Jeaneen Andorf; Abbot F Clark; Val C Sheffield; Thomas L Casavant; Todd E Scheetz; Edwin M Stone; Terry A Braun

doi:10.1142/S0219720007003132

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Transcript annotation prioritization and screening system (TrAPSS) for mutation screening

Journal article

Peer reviewed

Transcript annotation prioritization and screening system (TrAPSS) for mutation screening

Brian M O'Leary, Steven G Davis, Michael F Smith, Bartley Brown, Mathew B Kemp, Hakeem Almabrazi, Jason A Grundstad, Thomas Burns, Vladimir Leontiev, Jeaneen Andorf, …

Journal of bioinformatics and computational biology, Vol.5(6), pp.1155-1172

12/2007

DOI: 10.1142/S0219720007003132

PMID: 18172923

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Abstract

When searching for disease-causing mutations with polymerase chain reaction (PCR)-based methods, candidate genes are usually screened in their entirety, exon by exon. Genomic resources (i.e. www.ncbi.nih.gov, www.ensembl.org, and genome.ucsc.edu) largely support this paradigm for mutation screening by making it easy to view and access sequence data associated with genes in their genomic context. However, the administrative burden of conducting mutation screening in potentially hundreds of genes and thousands of exons in thousands of patients is significant, even with the use of public genome resources. For example, the manual design of oligonucleotide primers for all exons of the 10 Leber's congenital amaurosis (LCA) genes (149 exons) represents a significant information management challenge. The Transcript Annotation Prioritization and Screening System (TrAPSS) is designed to accelerate mutation screening by (1) providing a gene-based local cache of candidate disease genes in a genomic context, (2) automating tasks associated with optimizing candidate disease gene screening and information management, and (3) providing the implementation of an algorithmic technique to utilize large amounts of heterogeneous genome annotation (e.g. conserved protein functional domains) so as to prioritize candidate genes.

Algorithms

Computational Biology

Mutation

Software

Genomics - statistics & numerical data

User-Computer Interface

Database Management Systems

Humans

Databases, Genetic

Details

Title: Subtitle: Transcript annotation prioritization and screening system (TrAPSS) for mutation screening
Creators: Brian M O'Leary - Coordinated Laboratory for Computational Genomics, University of Iowa, Iowa City, IA 52242, USA. boleary@eng.uiowa.edu
Steven G Davis
Michael F Smith
Bartley Brown
Mathew B Kemp
Hakeem Almabrazi
Jason A Grundstad
Thomas Burns
Vladimir Leontiev
Jeaneen Andorf
Abbot F Clark
Val C Sheffield
Thomas L Casavant
Todd E Scheetz
Edwin M Stone
Terry A Braun
Resource Type: Journal article
Publication Details: Journal of bioinformatics and computational biology, Vol.5(6), pp.1155-1172
DOI: 10.1142/S0219720007003132
PMID: 18172923
NLM abbreviation: J Bioinform Comput Biol
ISSN: 0219-7200
eISSN: 1757-6334
Publisher: Singapore
Language: English
Date published: 12/2007
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Stead Family Department of Pediatrics; The University of Iowa Institute for Vision Research; Iowa Neuroscience Institute; Medical Genetics and Genomics; Ophthalmology and Visual Sciences
Record Identifier: 9983979946302771

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