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  • Kristiansson, Erik,1978Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, matematisk statistik,Department of Mathematical Sciences, Mathematical Statistics,University of Gothenburg,Chalmers tekniska högskola,Chalmers University of Technology (author)

A novel method for cross-species gene expression analysis

  • Article/chapterEnglish2013

Publisher, publication year, extent ...

  • 2013-02-27
  • Springer Science and Business Media LLC,2013
  • electronicrdacarrier

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  • LIBRIS-ID:oai:gup.ub.gu.se/178615
  • https://gup.ub.gu.se/publication/178615URI
  • https://doi.org/10.1186/1471-2105-14-70DOI
  • https://research.chalmers.se/publication/178615URI

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  • Language:English

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  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

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  • Background Analysis of gene expression from different species is a powerful way to identify evolutionarily conserved transcriptional responses. However, due to evolutionary events such as gene duplication, there is no one-to-one correspondence between genes from different species which makes comparison of their expression profiles complex. Results In this paper we describe a new method for cross-species meta-analysis of gene expression. The method takes the homology structure between compared species into account and can therefore compare expression data from genes with any number of orthologs and paralogs. A simulation study shows that the proposed method results in a substantial increase in statistical power compared to previously suggested procedures. As a proof of concept, we analyzed microarray data from heat stress experiments performed in eight species and identified several well-known evolutionarily conserved transcriptional responses. The method was also applied to gene expression profiles from five studies of estrogen exposed fish and both known and potentially novel responses were identified. Conclusions The method described in this paper will further increase the potential and reliability of meta-analysis of gene expression profiles from evolutionarily distant species. The method has been implemented in R and is freely available at http://bioinformatics.math.chalmers.se/Xspecies/ webcite.

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  • Österlund, Tobias,1984Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)tobiaso (author)
  • Gunnarsson, Lina-Maria,1977Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för fysiologi,Institute of Neuroscience and Physiology, Department of Physiology,University of Gothenburg(Swepub:gu)xgunli (author)
  • Arne, GabriellaGothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för patologi,Institute of Biomedicine, Department of Pathology,University of Gothenburg(Swepub:gu)xarnga (author)
  • Larsson, D. G. Joakim,1969Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för infektionssjukdomar,Institute of Biomedicine, Department of Infectious Medicine,University of Gothenburg(Swepub:gu)xlarjo (author)
  • Nerman, Olle,1951Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, matematisk statistik,Department of Mathematical Sciences, Mathematical Statistics,University of Gothenburg,Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)nerman (author)
  • Göteborgs universitetInstitutionen för matematiska vetenskaper, matematisk statistik (creator_code:org_t)

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  • In:BMC Bioinformatics: Springer Science and Business Media LLC141471-2105

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