{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T05:26:44Z","timestamp":1776317204010,"version":"3.50.1"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":1607,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Comparative analyses of gene expression data from different species have become an important component of the study of molecular evolution. Thus methods are needed to estimate evolutionary distances between expression profiles, as well as a neutral reference to estimate selective pressure. Divergence between expression profiles of homologous genes is often calculated with Pearson's or Euclidean distance. Neutral divergence is usually inferred from randomized data. Despite being widely used, neither of these two steps has been well studied. Here, we analyze these methods formally and on real data, highlight their limitations and propose improvements.<\/jats:p>\n               <jats:p>Results: It has been demonstrated that Pearson's distance, in contrast to Euclidean distance, leads to underestimation of the expression similarity between homologous genes with a conserved uniform pattern of expression. Here, we first extend this study to genes with conserved, but specific pattern of expression. Surprisingly, we find that both Pearson's and Euclidean distances used as a measure of expression similarity between genes depend on the expression specificity of those genes. We also show that the Euclidean distance depends strongly on data normalization. Next, we show that the randomization procedure that is widely used to estimate the rate of neutral evolution is biased when broadly expressed genes are abundant in the data. To overcome this problem, we propose a novel randomization procedure that is unbiased with respect to expression profiles present in the datasets. Applying our method to the mouse and human gene expression data suggests significant gene expression conservation between these species.<\/jats:p>\n               <jats:p>Contact: \u00a0marc.robinson-rechavi@unil.ch; sven.bergmann@unil.ch<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts266","type":"journal-article","created":{"date-parts":[[2012,5,11]],"date-time":"2012-05-11T00:28:30Z","timestamp":1336696110000},"page":"1865-1872","source":"Crossref","is-referenced-by-count":19,"title":["Correcting for the bias due to expression specificity improves the estimation of constrained evolution of expression between mouse and human"],"prefix":"10.1093","volume":"28","author":[{"given":"Barbara","family":"Piasecka","sequence":"first","affiliation":[{"name":"1 Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, 2Department of Medical Genetics, University of Lausanne, 1005 Lausanne and 3Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland"},{"name":"1 Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, 2Department of Medical Genetics, University of Lausanne, 1005 Lausanne and 3Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland"},{"name":"1 Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, 2Department of Medical Genetics, University of Lausanne, 1005 Lausanne and 3Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marc","family":"Robinson-Rechavi","sequence":"additional","affiliation":[{"name":"1 Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, 2Department of Medical Genetics, University of Lausanne, 1005 Lausanne and 3Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland"},{"name":"1 Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, 2Department of Medical Genetics, University of Lausanne, 1005 Lausanne and 3Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sven","family":"Bergmann","sequence":"additional","affiliation":[{"name":"1 Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, 2Department of Medical Genetics, University of Lausanne, 1005 Lausanne and 3Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland"},{"name":"1 Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, 2Department of Medical Genetics, University of Lausanne, 1005 Lausanne and 3Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2012,5,9]]},"reference":[{"key":"2023012512432432200_B1","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1007\/978-3-540-69828-9_12","article-title":"Bgee: integrating and comparing heterogeneous transcriptome data among species","volume-title":"Data Integration in the Life Sciences","author":"Bastian","year":"2008"},{"key":"2023012512432432200_B2","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1186\/jbiol130","article-title":"Conservation of core gene expression in vertebrate tissues","volume":"8","author":"Chan","year":"2009","journal-title":"J. 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