BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Atkinson EG, Maihofer AX, Kanai M, Martin AR, Karczewski KJ, Santoro ML, Ulirsch JC, Kamatani Y, Okada Y, Finucane HK, Koenen KC, Nievergelt CM, Daly MJ, Neale BM. Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power. Nat Genet 2021;53:195-204. [PMID: 33462486 DOI: 10.1038/s41588-020-00766-y] [Cited by in Crossref: 52] [Cited by in F6Publishing: 54] [Article Influence: 52.0] [Reference Citation Analysis]
Number Citing Articles
1 Cahill ME, Montgomery RR. Analytical Approaches to Uncover Genetic Associations for Rare Outcomes: Lessons from West Nile Neuroinvasive Disease. Methods in Molecular Biology 2023. [DOI: 10.1007/978-1-0716-2760-0_17] [Reference Citation Analysis]
2 Zhou G, Chen T, Zhao H. SDPRX: A statistical method for cross-population prediction of complex traits. The American Journal of Human Genetics 2022. [DOI: 10.1016/j.ajhg.2022.11.007] [Reference Citation Analysis]
3 Gouveia MH, Bentley AR, Tarazona-santos E, Bustamante CD, Adeyemo AA, Rotimi CN, Shriner D. Unappreciated Subcontinental Admixture in Europeans and European Americans: Implications for Genetic Epidemiology Studies.. [DOI: 10.1101/2022.11.28.518227] [Reference Citation Analysis]
4 Derks EM, Thorp JG, Gerring ZF. Ten challenges for clinical translation in psychiatric genetics. Nat Genet 2022. [PMID: 36138228 DOI: 10.1038/s41588-022-01174-0] [Reference Citation Analysis]
5 Oriol Sabat B, Mas Montserrat D, Giro-I-Nieto X, Ioannidis AG. SALAI-Net: species-agnostic local ancestry inference network. Bioinformatics 2022;38:ii27-33. [PMID: 36124792 DOI: 10.1093/bioinformatics/btac464] [Reference Citation Analysis]
6 Nowbandegani PS, Wohns AW, Ballard JL, Lander ES, Bloemendal A, Neale BM, O’connor LJ. Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies.. [DOI: 10.1101/2022.09.06.506858] [Reference Citation Analysis]
7 Jacobs BM, Peter M, Giovannoni G, Noyce AJ, Morris HR, Dobson R. Towards a global view of multiple sclerosis genetics. Nat Rev Neurol 2022. [PMID: 36075979 DOI: 10.1038/s41582-022-00704-y] [Reference Citation Analysis]
8 Gorman BR, Voloudakis G, Igo RP, Kinzy T, Halladay CW, Bigdeli TB, Zeng B, Venkatesh S, Cooke Bailey JN, Crawford DC, Markianos K, Dong F, Schreiner P, Zhang W, Hadi T, Anger MD, Stockwell AD, Melles RB, Yin J, Choquet H, Kaye R, Patasova K, Patel PJ, Yaspan BL, Jorgenson E, Hysi PG, Lotery AJ, Gaziano JM, Tsao PS, Fliesler SJ, Sullivan JM, Greenberg PB, Wu W, Assimes TL, Pyarajan S, Roussos P, Peachey NS, Iyengar SK, VA Million Veteran Program, International AMD Genomics Consortium (IAMDGC). Distinctive cross-ancestry genetic architecture for age-related macular degeneration.. [DOI: 10.1101/2022.08.16.22278855] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
9 Hou K, Ding Y, Xu Z, Wu Y, Bhattacharya A, Mester R, Belbin G, Conti D, Darst BF, Fornage M, Gignoux C, Guo X, Haiman C, Kenny E, Kim M, Kooperberg C, Lange L, Manichaikul A, North KE, Nudelman N, Peters U, Rasmussen-torvik LJ, Rich SS, Rotter JI, Wheeler HE, Zhou Y, Sankararaman S, Pasaniuc B. Causal effects on complex traits are similar across segments of different continental ancestries within admixed individuals.. [DOI: 10.1101/2022.08.16.22278868] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
10 Khan AT, Gogarten SM, McHugh CP, Stilp AM, Sofer T, Bowers ML, Wong Q, Cupples LA, Hidalgo B, Johnson AD, McDonald MN, McGarvey ST, Taylor MRG, Fullerton SM, Conomos MP, Nelson SC. Recommendations on the use and reporting of race, ethnicity, and ancestry in genetic research: Experiences from the NHLBI TOPMed program. Cell Genom 2022;2:100155. [PMID: 36119389 DOI: 10.1016/j.xgen.2022.100155] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
11 Browning SR, Waples RK, Browning BL. Fast, accurate local ancestry inference with FLARE.. [DOI: 10.1101/2022.08.02.502540] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
12 Caliebe A, Tekola-Ayele F, Darst BF, Wang X, Song YE, Gui J, Sebro RA, Balding DJ, Saad M, Dubé MP; IGES ELSI Committee. Including diverse and admixed populations in genetic epidemiology research. Genet Epidemiol 2022. [PMID: 35842778 DOI: 10.1002/gepi.22492] [Reference Citation Analysis]
13 Avadhanam S, Williams AL. Simultaneous inference of parental admixture proportions and admixture times from unphased local ancestry calls. The American Journal of Human Genetics 2022. [DOI: 10.1016/j.ajhg.2022.06.016] [Reference Citation Analysis]
14 Ziyatdinov A, Torres J, Alegre-díaz J, Backman J, Mbatchou J, Turner M, Gaynor SM, Joseph T, Zou Y, Liu D, Wade R, Staples J, Panea R, Popov A, Bai X, Balasubramanian S, Habegger L, Lanche R, Lopez A, Maxwell E, Jones M, García-ortiz H, Ramirez-reyes R, Santacruz-benítez R, Nag A, Smith KR, Reppell M, Zöllner S, Jorgenson E, Salerno W, Petrovski S, Overton J, Reid J, Thornton T, Abecasis G, Berumen J, Orozco-orozco L, Collins R, Baras A, Hill MR, Emberson JR, Marchini J, Kuri-morales P, Tapia-conyer R, Regeneron Genetics Center. Genotyping, sequencing and analysis of 140,000 adults from the Mexico City Prospective Study.. [DOI: 10.1101/2022.06.26.495014] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
15 Atkinson EG, Bianchi SB, Ye GY, Martínez-Magaña JJ, Tietz GE, Montalvo-Ortiz JL, Giusti-Rodriguez P, Palmer AA, Sanchez-Roige S. Cross-ancestry genomic research: time to close the gap. Neuropsychopharmacology 2022. [PMID: 35739257 DOI: 10.1038/s41386-022-01365-7] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
16 Miao J, Guo H, Song G, Zhao Z, Hou L, Lu Q. Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics.. [DOI: 10.1101/2022.05.26.493528] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
17 Ruan Y, Lin YF, Feng YA, Chen CY, Lam M, Guo Z, He L, Sawa A, Martin AR, Qin S, Huang H, Ge T; Stanley Global Asia Initiatives. Improving polygenic prediction in ancestrally diverse populations. Nat Genet 2022. [PMID: 35513724 DOI: 10.1038/s41588-022-01054-7] [Cited by in Crossref: 24] [Cited by in F6Publishing: 32] [Article Influence: 24.0] [Reference Citation Analysis]
18 Schaid DJ, Sinnwell JP, Batzler A, McDonnell SK. Polygenic risk for prostate cancer: Decreasing relative risk with age but little impact on absolute risk. Am J Hum Genet 2022;109:900-8. [PMID: 35353984 DOI: 10.1016/j.ajhg.2022.03.008] [Reference Citation Analysis]
19 Li Z, Zhao W, Shang L, Mosley TH, Kardia SLR, Smith JA, Zhou X. METRO: Multi-ancestry transcriptome-wide association studies for powerful gene-trait association detection. Am J Hum Genet 2022;109:783-801. [PMID: 35334221 DOI: 10.1016/j.ajhg.2022.03.003] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
20 Morrill K, Hekman J, Li X, McClure J, Logan B, Goodman L, Gao M, Dong Y, Alonso M, Carmichael E, Snyder-Mackler N, Alonso J, Noh HJ, Johnson J, Koltookian M, Lieu C, Megquier K, Swofford R, Turner-Maier J, White ME, Weng Z, Colubri A, Genereux DP, Lord KA, Karlsson EK. Ancestry-inclusive dog genomics challenges popular breed stereotypes. Science 2022;376:eabk0639. [PMID: 35482869 DOI: 10.1126/science.abk0639] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 9.0] [Reference Citation Analysis]
21 Li B, Aouizerat BE, Cheng Y, Anastos K, Justice AC, Zhao H, Xu K. Incorporating local ancestry improves identification of ancestry-associated methylation signatures and meQTLs in African Americans. Commun Biol 2022;5:401. [PMID: 35488087 DOI: 10.1038/s42003-022-03353-5] [Reference Citation Analysis]
22 Asiimwe IG, Pirmohamed M. Ethnic Diversity and Warfarin Pharmacogenomics. Front Pharmacol 2022;13:866058. [PMID: 35444556 DOI: 10.3389/fphar.2022.866058] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
23 Gopalan S, Smith SP, Korunes K, Hamid I, Ramachandran S, Goldberg A. Human genetic admixture through the lens of population genomics. Phil Trans R Soc B 2022;377:20200410. [DOI: 10.1098/rstb.2020.0410] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
24 Conley AB, Rishishwar L, Ahmad M, Sharma S, Norris ET, Jordan IK, Mariño-ramírez L. Rye: genetic ancestry inference at biobank scale.. [DOI: 10.1101/2022.04.15.488477] [Reference Citation Analysis]
25 Fatumo S, Chikowore T, Choudhury A, Ayub M, Martin AR, Kuchenbaecker K. A roadmap to increase diversity in genomic studies. Nat Med 2022. [PMID: 35145307 DOI: 10.1038/s41591-021-01672-4] [Cited by in Crossref: 29] [Cited by in F6Publishing: 36] [Article Influence: 29.0] [Reference Citation Analysis]
26 Wendt FR, Pathak GA, Vahey J, Qin X, Koller D, Cabrera-mendoza B, Haeny A, Harrington KM, Rajeevan N, Duong LM, Levey DF, De Angelis F, De Lillo A, Bigdeli TB, Pyarajan S, Gaziano JM, Gelernter J, Aslan M, Provenzale D, Helmer DA, Hauser ER, Polimanti R, VA Million Veteran Program, Department of Veteran Affairs Cooperative Study Program (#2006). Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program.. [DOI: 10.1101/2022.01.24.477583] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
27 Moore A, Marks J, Quach BC, Guo Y, Bierut LJ, Gaddis NC, Hancock DB, Page GP, Johnson EO. Evaluation of methods incorporating biological function and GWAS summary statistics to accelerate discovery.. [DOI: 10.1101/2022.01.10.475153] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
28 Avadhanam S, Williams AL. Simultaneous inference of parental admixture proportions and admixture times from unphased local ancestry calls.. [DOI: 10.1101/2022.01.05.475139] [Reference Citation Analysis]
29 Perera MA, Hernandez W. GPCR Patient Drug Interaction—Pharmacogenetics: Genome-Wide Association Studies (GWAS). Comprehensive Pharmacology 2022. [DOI: 10.1016/b978-0-12-820472-6.00136-5] [Reference Citation Analysis]
30 Gao G, Zhao F, Ahearn TU, Lunetta KL, Troester MA, Du Z, Ogundiran TO, Ojengbede O, Blot W, Nathanson KL, Domchek SM, Nemesure B, Hennis A, Ambs S, Mcclellan J, Nie M, Bertrand K, Zirpoli G, Yao S, Olshan AF, Bensen JT, Bandera EV, Nyante S, Conti DV, Press MF, Ingles SA, John EM, Bernstein L, Hu JJ, Deming-halverson SL, Chanock SJ, Ziegler RG, Rodriguez-gil JL, Sucheston-campbell LE, Sandler DP, Taylor JA, Kitahara CM, O’brien KM, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PD, Wang Q, Figueroa J, Biritwum R, Adjei E, Wiafe S, Ambrosone CB, Zheng W, Olopade OI, García-closas M, Palmer JR, Haiman CA, Huo D, GBHS Study Team. Polygenic Risk Scores for Prediction of Breast Cancer Risk in Women of African Ancestry: a Cross-Ancestry Approach.. [DOI: 10.1101/2021.12.16.21266424] [Reference Citation Analysis]
31 Sohail M, Izarraras-Gomez A, Ortega-Del Vecchyo D. Populations, Traits, and Their Spatial Structure in Humans. Genome Biol Evol 2021;13:evab272. [PMID: 34894236 DOI: 10.1093/gbe/evab272] [Reference Citation Analysis]
32 Hou K, Bhattacharya A, Mester R, Burch KS, Pasaniuc B. On powerful GWAS in admixed populations. Nat Genet 2021;53:1631-3. [PMID: 34824480 DOI: 10.1038/s41588-021-00953-5] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
33 Atkinson EG, Bloemendal A, Maihofer AX, Nievergelt CM, Daly MJ, Neale BM. Reply to: On powerful GWAS in admixed populations. Nat Genet 2021;53:1634-5. [PMID: 34824479 DOI: 10.1038/s41588-021-00975-z] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
34 Simonin-Wilmer I, Orozco-Del-Pino P, Bishop DT, Iles MM, Robles-Espinoza CD. An Overview of Strategies for Detecting Genotype-Phenotype Associations Across Ancestrally Diverse Populations. Front Genet 2021;12:703901. [PMID: 34804113 DOI: 10.3389/fgene.2021.703901] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
35 Wang Y, Namba S, Lopera E, Kerminen S, Tsuo K, Läll K, Kanai M, Zhou W, Wu K, Favé M, Bhatta L, Awadalla P, Brumpton B, Deelen P, Hveem K, Lo Faro V, Mägi R, Murakami Y, Sanna S, Smoller JW, Uzunovic J, Wolford BN, Willer C, Gamazon ER, Cox NJ, Surakka I, Okada Y, Martin AR, Hirbo J, Global Biobank Meta-analysis Initiative. Global biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts.. [DOI: 10.1101/2021.11.18.21266545] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 10.0] [Reference Citation Analysis]
36 Mortezaei Z, Tavallaei M. Recent innovations and in-depth aspects of post-genome wide association study (Post-GWAS) to understand the genetic basis of complex phenotypes. Heredity (Edinb) 2021;127:485-97. [PMID: 34689168 DOI: 10.1038/s41437-021-00479-w] [Cited by in Crossref: 6] [Cited by in F6Publishing: 8] [Article Influence: 6.0] [Reference Citation Analysis]
37 Saxenhofer M, Labutin A, White TA, Heckel G. Host genetic factors associated with the range limit of a European hantavirus. Mol Ecol 2022;31:252-65. [PMID: 34614264 DOI: 10.1111/mec.16211] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
38 Passamonti MM, Somenzi E, Barbato M, Chillemi G, Colli L, Joost S, Milanesi M, Negrini R, Santini M, Vajana E, Williams JL, Ajmone-Marsan P. The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock. Animals (Basel) 2021;11:2833. [PMID: 34679854 DOI: 10.3390/ani11102833] [Cited by in Crossref: 5] [Cited by in F6Publishing: 8] [Article Influence: 5.0] [Reference Citation Analysis]
39 Maihofer AX, Choi KW, Coleman JRI, Daskalakis NP, Denckla CA, Ketema E, Morey RA, Polimanti R, Ratanatharathorn A, Torres K, Wingo AP, Zai CC, Aiello AE, Almli LM, Amstadter AB, Andersen SB, Andreassen OA, Arbisi PA, Ashley-Koch AE, Austin SB, Avdibegović E, Borglum AD, Babić D, Bækvad-Hansen M, Baker DG, Beckham JC, Bierut LJ, Bisson JI, Boks MP, Bolger EA, Bradley B, Brashear M, Breen G, Bryant RA, Bustamante AC, Bybjerg-Grauholm J, Calabrese JR, Caldas-de-Almeida JM, Chen CY, Dale AM, Dalvie S, Deckert J, Delahanty DL, Dennis MF, Disner SG, Domschke K, Duncan LE, Džubur Kulenović A, Erbes CR, Evans A, Farrer LA, Feeny NC, Flory JD, Forbes D, Franz CE, Galea S, Garrett ME, Gautam A, Gelaye B, Gelernter J, Geuze E, Gillespie CF, Goçi A, Gordon SD, Guffanti G, Hammamieh R, Hauser MA, Heath AC, Hemmings SMJ, Hougaard DM, Jakovljević M, Jett M, Johnson EO, Jones I, Jovanovic T, Qin XJ, Karstoft KI, Kaufman ML, Kessler RC, Khan A, Kimbrel NA, King AP, Koen N, Kranzler HR, Kremen WS, Lawford BR, Lebois LAM, Lewis C, Liberzon I, Linnstaedt SD, Logue MW, Lori A, Lugonja B, Luykx JJ, Lyons MJ, Maples-Keller JL, Marmar C, Martin NG, Maurer D, Mavissakalian MR, McFarlane A, McGlinchey RE, McLaughlin KA, McLean SA, Mehta D, Mellor R, Michopoulos V, Milberg W, Miller MW, Morris CP, Mors O, Mortensen PB, Nelson EC, Nordentoft M, Norman SB, O'Donnell M, Orcutt HK, Panizzon MS, Peters ES, Peterson AL, Peverill M, Pietrzak RH, Polusny MA, Rice JP, Risbrough VB, Roberts AL, Rothbaum AO, Rothbaum BO, Roy-Byrne P, Ruggiero KJ, Rung A, Rutten BPF, Saccone NL, Sanchez SE, Schijven D, Seedat S, Seligowski AV, Seng JS, Sheerin CM, Silove D, Smith AK, Smoller JW, Sponheim SR, Stein DJ, Stevens JS, Teicher MH, Thompson WK, Trapido E, Uddin M, Ursano RJ, van den Heuvel LL, Van Hooff M, Vermetten E, Vinkers C, Voisey J, Wang Y, Wang Z, Werge T, Williams MA, Williamson DE, Winternitz S, Wolf C, Wolf EJ, Yehuda R, Young KA, Young RM, Zhao H, Zoellner LA, Haas M, Lasseter H, Provost AC, Salem RM, Sebat J, Shaffer RA, Wu T, Ripke S, Daly MJ, Ressler KJ, Koenen KC, Stein MB, Nievergelt CM. Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information. Biol Psychiatry 2021:S0006-3223(21)01632-2. [PMID: 34865855 DOI: 10.1016/j.biopsych.2021.09.020] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
40 Hilmarsson H, Kumar AS, Rastogi R, Bustamante CD, Montserrat DM, Ioannidis AG. High Resolution Ancestry Deconvolution for Next Generation Genomic Data.. [DOI: 10.1101/2021.09.19.460980] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
41 McInnes G, Yee SW, Pershad Y, Altman RB. Genomewide Association Studies in Pharmacogenomics. Clin Pharmacol Ther 2021;110:637-48. [PMID: 34185318 DOI: 10.1002/cpt.2349] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 9.0] [Reference Citation Analysis]
42 Muse ED, Chen SF, Torkamani A. Monogenic and Polygenic Models of Coronary Artery Disease. Curr Cardiol Rep 2021;23:107. [PMID: 34196841 DOI: 10.1007/s11886-021-01540-0] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
43 Suarez-Pajes E, Díaz-de Usera A, Marcelino-Rodríguez I, Guillen-Guio B, Flores C. Genetic Ancestry Inference and Its Application for the Genetic Mapping of Human Diseases. Int J Mol Sci 2021;22:6962. [PMID: 34203440 DOI: 10.3390/ijms22136962] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
44 Schultz LM, Merikangas AK, Ruparel K, Jacquemont S, Glahn DC, Gur RE, Barzilay R, Almasy L. Stability of Polygenic Scores Across Discovery Genome-Wide Association Studies.. [DOI: 10.1101/2021.06.18.449060] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
45 Lin M, Park DS, Zaitlen NA, Henn BM, Gignoux CR. Admixed Populations Improve Power for Variant Discovery and Portability in Genome-Wide Association Studies. Front Genet 2021;12:673167. [PMID: 34108994 DOI: 10.3389/fgene.2021.673167] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 6.0] [Reference Citation Analysis]
46 Lin M, Park DS, Zaitlen NA, Henn BM, Gignoux CR. Admixed Populations Improve Power for Variant Discovery and Portability in Genome-wide Association Studies.. [DOI: 10.1101/2021.03.09.434643] [Reference Citation Analysis]
47 Osikoya O, Axton M. The missing person in gene‐environment interactions. Advanced Genetics 2021;2. [DOI: 10.1002/ggn2.10041] [Reference Citation Analysis]
48 Clyde D. Addressing admixture with Tractor. Nat Rev Genet 2021;22:134. [PMID: 33504950 DOI: 10.1038/s41576-021-00333-z] [Reference Citation Analysis]