Linked Life Data

18052916

Source:http://linkedlifedata.com/resource/pubmed/id/18052916

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2007-12-6
pubmed:abstractText
Characterizing genetic variability in the human pathogenic Plasmodium species, the group of parasites that cause Malaria, may have broad global health implications. Specifically, discerning the combinations of mutations that lead to viable parasites and the population level frequencies of these clonal sequences will allow for targeted vaccine development and individualized treatment choices. This presents an analytical challenge, however, since haplotypic phase (i.e. the alignment of bases on a single DNA strand) is generally unobservable in multiply infected individuals. This manuscript describes an expectation maximization (EM) approach to maximum likelihood estimation of haplotype frequencies in this missing data setting. The approach is applied to a cohort of N=341 malaria infected children in Uganda, Cameroon and Sudan to characterize regional differences. A simulation study is also presented to characterize method performance and assess sensitivity to distributional assumptions.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1544-6115
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
Article33
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
An expectation maximization approach to estimate malaria haplotype frequencies in multiply infected children.
pubmed:affiliation
University of Massachusetts, Amherst, MA, USA. xiaohong@schoolph.umass.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural