Linked Life Data

19322152

Source:http://linkedlifedata.com/resource/pubmed/id/19322152

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2009-3-26
pubmed:abstractText
Sequence analysis of the mitochondrial genome has become a routine method in the study of mitochondrial diseases. Quite often, the sequencing efforts in the search of pathogenic or disease-associated mutations are affected by technical and interpretive problems, caused by sample mix-up, contamination, biochemical problems, incomplete sequencing, misdocumentation and insufficient reference to previously published data. To assess data quality in case studies of mitochondrial diseases, it is recommended to compare any mtDNA sequence under consideration to their phylogenetically closest lineages available in the Web. The median network method has proven useful for visualizing potential problems with the data. We contrast some early reports of complete mtDNA sequences to more recent total mtDNA sequencing efforts in studies of various mitochondrial diseases. We conclude that the quality of complete mtDNA sequences generated in the medical field in the past few years is somewhat unsatisfactory and may even fall behind that of pioneer manual sequencing in the early nineties. Our study provides a paradigm for an a posteriori evaluation of sequence quality and for detection of potential problems with inferring a pathogenic status of a particular mutation.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1435-232X
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
54
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
174-81
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Median network analysis of defectively sequenced entire mitochondrial genomes from early and contemporary disease studies.
pubmed:affiliation
Department of Mathematics, University of Hamburg, Hamburg, Germany. bandelt@math.uni-hamburg.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't