{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T16:21:55Z","timestamp":1770567715101,"version":"3.49.0"},"reference-count":26,"publisher":"Oxford University Press (OUP)","issue":"22","license":[{"start":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T00:00:00Z","timestamp":1664496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Center of Information Technology"},{"DOI":"10.13039\/501100001721","name":"University of Groningen","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001721","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003246","name":"NWO","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,11,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Gaussian graphical models (GGMs) are network representations of random variables (as nodes) and their partial correlations (as edges). GGMs overcome the challenges of high-dimensional data analysis by using shrinkage methodologies. Therefore, they have become useful to reconstruct gene regulatory networks from gene-expression profiles. However, it is often ignored that the partial correlations are \u2018shrunk\u2019 and that they cannot be compared\/assessed directly. Therefore, accurate (differential) network analyses need to account for the number of variables, the sample size, and also the shrinkage value, otherwise, the analysis and its biological interpretation would turn biased. To date, there are no appropriate methods to account for these factors and address these issues.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We derive the statistical properties of the partial correlation obtained with the Ledoit\u2013Wolf shrinkage. Our result provides a toolbox for (differential) network analyses as (i) confidence intervals, (ii) a test for zero partial correlation (null-effects) and (iii) a test to compare partial correlations. Our novel (parametric) methods account for the number of variables, the sample size and the shrinkage values. Additionally, they are computationally fast, simple to implement and require only basic statistical knowledge. Our simulations show that the novel tests perform better than DiffNetFDR\u2014a recently published alternative\u2014in terms of the trade-off between true and false positives. The methods are demonstrated on synthetic data and two gene-expression datasets from Escherichia coli and Mus musculus.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The R package with the methods and the R script with the analysis are available in https:\/\/github.com\/V-Bernal\/GeneNetTools.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac657","type":"journal-article","created":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T19:47:31Z","timestamp":1664567251000},"page":"5049-5054","source":"Crossref","is-referenced-by-count":3,"title":["GeneNetTools: tests for Gaussian graphical models with shrinkage"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9134-7186","authenticated-orcid":false,"given":"Victor","family":"Bernal","sequence":"first","affiliation":[{"name":"Center of Information Technology, University of Groningen , Groningen 9747 AJ, The Netherlands"},{"name":"Department of Mathematics, Bernoulli Institute, University of Groningen , Groningen 9747 AG, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Venustiano","family":"Soancatl-Aguilar","sequence":"additional","affiliation":[{"name":"Center of Information Technology, University of Groningen , Groningen 9747 AJ, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonas","family":"Bulthuis","sequence":"additional","affiliation":[{"name":"Center of Information Technology, University of Groningen , Groningen 9747 AJ, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Victor","family":"Guryev","sequence":"additional","affiliation":[{"name":"European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen , Groningen 9713 AV, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2218-1140","authenticated-orcid":false,"given":"Peter","family":"Horvatovich","sequence":"additional","affiliation":[{"name":"Department of Analytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen , Groningen 9713 AV, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Grzegorczyk","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Bernoulli Institute, University of Groningen , Groningen 9747 AG, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,9,30]]},"reference":[{"key":"2022112014194961500_btac657-B1","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/nrg2918","article-title":"An integrative systems medicine approach to mapping human metabolic diseases","volume":"12","author":"Barab\u00e1si","year":"2011","journal-title":"Nat. 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