Linked Life Data

20138981

Source:http://linkedlifedata.com/resource/pubmed/id/20138981

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2010-4-2
pubmed:abstractText
Sequence capture methods for targeted next generation sequencing promise to massively reduce cost of genomics projects compared to untargeted sequencing. However, evaluated capture methods specifically dedicated to biologically relevant genomic regions are rare. Whole exome capture has been shown to be a powerful tool to discover the genetic origin of disease and provides a reduction in target size and thus calculative sequencing capacity of >90-fold compared to untargeted whole genome sequencing. For further cost reduction, a valuable complementing approach is the analysis of smaller, relevant gene subsets but involving large cohorts of samples. However, effective adjustment of target sizes and sample numbers is hampered by the limited scalability of enrichment systems. We report a highly scalable and automated method to capture a 480 Kb exome subset of 115 cancer-related genes using microfluidic DNA arrays. The arrays are adaptable from 125 Kb to 1 Mb target size and/or one to eight samples without barcoding strategies, representing a further 26 - 270-fold reduction of calculative sequencing capacity compared to whole exome sequencing. Illumina GAII analysis of a HapMap genome enriched for this exome subset revealed a completeness of >96%. Uniformity was such that >68% of exons had at least half the median depth of coverage. An analysis of reference SNPs revealed a sensitivity of up to 93% and a specificity of 98.2% or higher.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1089-8646
pubmed:author
pubmed:copyrightInfo
Copyright 2010 Elsevier Inc. All rights reserved.
pubmed:issnType
Electronic
pubmed:volume
95
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
241-6
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Targeted high throughput sequencing of a cancer-related exome subset by specific sequence capture with a fully automated microarray platform.
pubmed:affiliation
febit biomed gmbh, Im Neuenheimer Feld 519, 69120 Heidelberg, Germany. daniel.summerer@febit.de
pubmed:publicationType
Journal Article