MOTIVATION: Sample mix-ups can arise during sample collection, handling, genotyping or data management. It is unclear how often sample mix-ups occur in genome-wide studies, as there currently are no post hoc methods that can identify these mix-ups in unrelated samples. We have therefore developed an algorithm (MixupMapper) that can both detect and correct sample mix-ups in genome-wide studies that study gene expression levels. RESULTS: We applied MixupMapper to five publicly available human genetical genomics datasets. On average, 3% of all analyzed samples had been assigned incorrect expression phenotypes: in one of the datasets 23% of the samples had incorrect expression phenotypes. The consequences of sample mix-ups are substantial: when we corrected these sample mix-ups, we identified on average 15% more significant cis-expression quantitative trait loci (cis-eQTLs). In one dataset, we identified three times as many significant cis-eQTLs after correction. Furthermore, we show through simulations that sample mix-ups can lead to an underestimation of the explained heritability of complex traits in genome-wide association datasets. AVAILABILITY AND IMPLEMENTATION: MixupMapper is freely available at http://www.genenetwork.nl/mixupmapper/
MOTIVATION: Sample mix-ups can arise during sample collection, handling, genotyping or data management. It is unclear how often sample mix-ups occur in genome-wide studies, as there currently are no post hoc methods that can identify these mix-ups in unrelated samples. We have therefore developed an algorithm (MixupMapper) that can both detect and correct sample mix-ups in genome-wide studies that study gene expression levels. RESULTS: We applied MixupMapper to five publicly available human genetical genomics datasets. On average, 3% of all analyzed samples had been assigned incorrect expression phenotypes: in one of the datasets 23% of the samples had incorrect expression phenotypes. The consequences of sample mix-ups are substantial: when we corrected these sample mix-ups, we identified on average 15% more significant cis-expression quantitative trait loci (cis-eQTLs). In one dataset, we identified three times as many significant cis-eQTLs after correction. Furthermore, we show through simulations that sample mix-ups can lead to an underestimation of the explained heritability of complex traits in genome-wide association datasets. AVAILABILITY AND IMPLEMENTATION: MixupMapper is freely available at http://www.genenetwork.nl/mixupmapper/
Authors: Peter A C 't Hoen; Marc R Friedländer; Jonas Almlöf; Michael Sammeth; Irina Pulyakhina; Seyed Yahya Anvar; Jeroen F J Laros; Henk P J Buermans; Olof Karlberg; Mathias Brännvall; Johan T den Dunnen; Gert-Jan B van Ommen; Ivo G Gut; Roderic Guigó; Xavier Estivill; Ann-Christine Syvänen; Emmanouil T Dermitzakis; Tuuli Lappalainen Journal: Nat Biotechnol Date: 2013-09-15 Impact factor: 54.908
Authors: Michael D Edge; Bridget F B Algee-Hewitt; Trevor J Pemberton; Jun Z Li; Noah A Rosenberg Journal: Proc Natl Acad Sci U S A Date: 2017-05-15 Impact factor: 11.205
Authors: Marc Jan Bonder; René Luijk; Daria V Zhernakova; Matthijs Moed; Patrick Deelen; Martijn Vermaat; Maarten van Iterson; Freerk van Dijk; Michiel van Galen; Jan Bot; Roderick C Slieker; P Mila Jhamai; Michael Verbiest; H Eka D Suchiman; Marijn Verkerk; Ruud van der Breggen; Jeroen van Rooij; Nico Lakenberg; Wibowo Arindrarto; Szymon M Kielbasa; Iris Jonkers; Peter van 't Hof; Irene Nooren; Marian Beekman; Joris Deelen; Diana van Heemst; Alexandra Zhernakova; Ettje F Tigchelaar; Morris A Swertz; Albert Hofman; André G Uitterlinden; René Pool; Jenny van Dongen; Jouke J Hottenga; Coen D A Stehouwer; Carla J H van der Kallen; Casper G Schalkwijk; Leonard H van den Berg; Erik W van Zwet; Hailiang Mei; Yang Li; Mathieu Lemire; Thomas J Hudson; P Eline Slagboom; Cisca Wijmenga; Jan H Veldink; Marleen M J van Greevenbroek; Cornelia M van Duijn; Dorret I Boomsma; Aaron Isaacs; Rick Jansen; Joyce B J van Meurs; Peter A C 't Hoen; Lude Franke; Bastiaan T Heijmans Journal: Nat Genet Date: 2016-12-05 Impact factor: 38.330
Authors: Daria V Zhernakova; Patrick Deelen; Martijn Vermaat; Maarten van Iterson; Michiel van Galen; Wibowo Arindrarto; Peter van 't Hof; Hailiang Mei; Freerk van Dijk; Harm-Jan Westra; Marc Jan Bonder; Jeroen van Rooij; Marijn Verkerk; P Mila Jhamai; Matthijs Moed; Szymon M Kielbasa; Jan Bot; Irene Nooren; René Pool; Jenny van Dongen; Jouke J Hottenga; Coen D A Stehouwer; Carla J H van der Kallen; Casper G Schalkwijk; Alexandra Zhernakova; Yang Li; Ettje F Tigchelaar; Niek de Klein; Marian Beekman; Joris Deelen; Diana van Heemst; Leonard H van den Berg; Albert Hofman; André G Uitterlinden; Marleen M J van Greevenbroek; Jan H Veldink; Dorret I Boomsma; Cornelia M van Duijn; Cisca Wijmenga; P Eline Slagboom; Morris A Swertz; Aaron Isaacs; Joyce B J van Meurs; Rick Jansen; Bastiaan T Heijmans; Peter A C 't Hoen; Lude Franke Journal: Nat Genet Date: 2016-12-05 Impact factor: 38.330
Authors: Chelsea K Raulerson; Arthur Ko; John C Kidd; Kevin W Currin; Sarah M Brotman; Maren E Cannon; Ying Wu; Cassandra N Spracklen; Anne U Jackson; Heather M Stringham; Ryan P Welch; Christian Fuchsberger; Adam E Locke; Narisu Narisu; Aldons J Lusis; Mete Civelek; Terrence S Furey; Johanna Kuusisto; Francis S Collins; Michael Boehnke; Laura J Scott; Dan-Yu Lin; Michael I Love; Markku Laakso; Päivi Pajukanta; Karen L Mohlke Journal: Am J Hum Genet Date: 2019-09-26 Impact factor: 11.025
Authors: Xiaoling Zhang; Hinco J Gierman; Daniel Levy; Andrew Plump; Radu Dobrin; Harald H H Goring; Joanne E Curran; Matthew P Johnson; John Blangero; Stuart K Kim; Christopher J O'Donnell; Valur Emilsson; Andrew D Johnson Journal: BMC Genomics Date: 2014-06-27 Impact factor: 3.969
Authors: Yvonne Shao; McKenzie Shaw; Kaitlin Todd; Maria Khrestian; Giana D'Aleo; P John Barnard; Jeff Zahratka; Jagan Pillai; Chang-En Yu; C Dirk Keene; James B Leverenz; Lynn M Bekris Journal: J Hum Genet Date: 2018-01-25 Impact factor: 3.172