Linked Life Data

21254222

Source:http://linkedlifedata.com/resource/pubmed/id/21254222

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2011-3-11
pubmed:abstractText
The advent of next-generation sequencing technologies has facilitated the detection of rare variants. Despite the significant cost reduction, sequencing cost is still high for large-scale studies. In this article, we examine DNA pooling as a cost-effective strategy for rare variant detection. We consider the optimal number of individuals in a DNA pool to detect an allele with a specific minor allele frequency (MAF) under a given coverage depth and detection threshold. We found that the optimal number of individuals in a pool is indifferent to the MAF at the same coverage depth and detection threshold. In addition, when the individual contributions to each pool are equal, the total number of individuals across different pools required in an optimal design to detect a variant with a desired power is similar at different coverage depths. When the contributions are more variable, more individuals tend to be needed for higher coverage depths. Our study provides general guidelines on using DNA pooling for more cost-effective identifications of rare variants.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1098-2272
pubmed:author
pubmed:copyrightInfo
© 2011 Wiley-Liss, Inc.
pubmed:issnType
Electronic
pubmed:volume
35
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
139-47
pubmed:dateRevised
2011-9-22
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
On optimal pooling designs to identify rare variants through massive resequencing.
pubmed:affiliation
Department of Epidemiology and Public Health, Yale University, New Haven, Connecticut, USA. joonsang.lee@yale.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural