uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Data rotation improves genomotyping efficiency
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
Show others and affiliations
2005 (English)In: Biometrical Journal, ISSN 0323-3847, E-ISSN 1521-4036, Vol. 47, no 4, 585-598 p.Article in journal (Refereed) Published
Abstract [en]

Unsequenced bacterial strains can be characterized by comparing their genomic DNA to a sequenced reference genome of the same species. This comparative genomic approach, also called genomotyping, is leading to an increased understanding of bacterial evolution and pathogenesis. It is efficiently accomplished by comparative genomic hybridization on custom-designed cDNA microarrays. The microarray experiment results in fluorescence intensities for reference and sample genome for each gene. The logratio of these intensities is usually compared to a cut-off, classifying each gene of the sample genome as a candidate for an absent or present gene with respect to the reference genome. Reducing the usually high rate of false positives in the list of candidates for absent genes is decisive for both time and costs of the experiment. We propose a novel method to improve efficiency of genomotyping experiments in this sense, by rotating the normalized intensity data before setting up the list of candidate genes. We analyze simulated genomotyping data and also re-analyze an experimental data set for comparison and illustration. We approximately halve the proportion of false positives in the list of candidate absent genes for the example comparative genomic hybridization experiment as well as for the simulation experiments.

Place, publisher, year, edition, pages
2005. Vol. 47, no 4, 585-598 p.
Keyword [en]
Algorithms, Chromosome Mapping/*methods, Computer Simulation, Data Interpretation; Statistical, Genome; Bacterial, Genotype, In Situ Hybridization; Fluorescence/*methods, Models; Genetic, Models; Statistical, Oligonucleotide Array Sequence Analysis/*methods, Reproducibility of Results, Sensitivity and Specificity
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:uu:diva-80773DOI: 10.1002/bimj.200410160PubMedID: 16161813OAI: oai:DiVA.org:uu-80773DiVA: diva2:108687
Available from: 2006-05-24 Created: 2006-05-24 Last updated: 2011-02-18Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Authority records BETA

Lindroos, HilleviAndersson, Siv

Search in DiVA

By author/editor
Lindroos, HilleviAndersson, Siv
By organisation
Molecular Evolution
In the same journal
Biometrical Journal
Biological Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 496 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf