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PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2004-10-11
pubmed:abstractText
Identifying changepoints is an important problem in molecular genetics. Our motivating example is from cancer genetics where interest focuses on identifying areas of a chromosome with an increased likelihood of a tumor suppressor gene. Loss of heterozygosity (LOH) is a binary measure of allelic loss in which abrupt changes in LOH frequency along the chromosome may identify boundaries indicative of a region containing a tumor suppressor gene. Our interest was on testing for the presence of multiple changepoints in order to identify regions of increased LOH frequency. A complicating factor is the substantial heterogeneity in LOH frequency across patients, where some patients have a very high LOH frequency while others have a low frequency. We develop a procedure for identifying multiple changepoints in heterogeneous binary data. We propose both approximate and full maximum-likelihood approaches and compare these two approaches with a naive approach in which we ignore the heterogeneity in the binary data. The methodology is used to estimate the pattern in LOH frequency on chromosome 13 in esophageal cancer patients and to isolate an area of inflated LOH frequency on chromosome 13 which may contain a tumor suppressor gene. Using simulations, we show that our approach works well and that it is robust to departures from some key modeling assumptions.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1465-4644
pubmed:author
pubmed:issnType
Print
pubmed:volume
5
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
515-29
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Identifying multiple changepoints in heterogeneous binary data with an application to molecular genetics.
pubmed:affiliation
Biometric Research Branch, National Cancer Institute, 6130 Executive Blvd, Room 8136, Bethesda, MD 20892, USA.
pubmed:publicationType
Journal Article