 Connection
Christopher Gignoux to Quantitative Trait Loci
This is a "connection" page, showing publications Christopher Gignoux has written about Quantitative Trait Loci.
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Connection Strength |
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0.316 |
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Keys KL, Mak ACY, White MJ, Eckalbar WL, Dahl AW, Mefford J, Mikhaylova AV, Contreras MG, Elhawary JR, Eng C, Hu D, Huntsman S, Oh SS, Salazar S, Lenoir MA, Ye JC, Thornton TA, Zaitlen N, Burchard EG, Gignoux CR. On the cross-population generalizability of gene expression prediction models. PLoS Genet. 2020 08; 16(8):e1008927.
Score: 0.154
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Anwar MY, Graff M, Highland HM, Smit R, Wang Z, Buchanan VL, Young KL, Kenny EE, Fernandez-Rhodes L, Liu S, Assimes T, Garcia DO, Daeeun K, Gignoux CR, Justice AE, Haiman CA, Buyske S, Peters U, Loos RJF, Kooperberg C, North KE. Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts. Hum Genet. 2023 Oct; 142(10):1477-1489.
Score: 0.048
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Araujo DS, Nguyen C, Hu X, Mikhaylova AV, Gignoux C, Ardlie K, Taylor KD, Durda P, Liu Y, Papanicolaou G, Cho MH, Rich SS, Rotter JI, Im HK, Manichaikul A, Wheeler HE. Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations. HGG Adv. 2023 Oct 12; 4(4):100216.
Score: 0.047
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Schubert R, Geoffroy E, Gregga I, Mulford AJ, Aguet F, Ardlie K, Gerszten R, Clish C, Van Den Berg D, Taylor KD, Durda P, Johnson WC, Cornell E, Guo X, Liu Y, Tracy R, Conomos M, Blackwell T, Papanicolaou G, Lappalainen T, Mikhaylova AV, Thornton TA, Cho MH, Gignoux CR, Lange L, Lange E, Rich SS, Rotter JI, Manichaikul A, Im HK, Wheeler HE. Protein prediction for trait mapping in diverse populations. PLoS One. 2022; 17(2):e0264341.
Score: 0.043
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Kidd JM, Sharpton TJ, Bobo D, Norman PJ, Martin AR, Carpenter ML, Sikora M, Gignoux CR, Nemat-Gorgani N, Adams A, Guadalupe M, Guo X, Feng Q, Li Y, Liu X, Parham P, Hoal EG, Feldman MW, Pollard KS, Wall JD, Bustamante CD, Henn BM. Exome capture from saliva produces high quality genomic and metagenomic data. BMC Genomics. 2014 Apr 04; 15:262.
Score: 0.025
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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