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Items: 1 to 20 of 106

1.

Local exome sequences facilitate imputation of less common variants and increase power of genome wide association studies.

Joshi PK, Prendergast J, Fraser RM, Huffman JE, Vitart V, Hayward C, McQuillan R, Glodzik D, Polašek O, Hastie ND, Rudan I, Campbell H, Wright AF, Haley CS, Wilson JF, Navarro P.

PLoS One. 2013 Jul 16;8(7):e68604. doi: 10.1371/journal.pone.0068604. Print 2013.

2.

Rare variant genotype imputation with thousands of study-specific whole-genome sequences: implications for cost-effective study designs.

Pistis G, Porcu E, Vrieze SI, Sidore C, Steri M, Danjou F, Busonero F, Mulas A, Zoledziewska M, Maschio A, Brennan C, Lai S, Miller MB, Marcelli M, Urru MF, Pitzalis M, Lyons RH, Kang HM, Jones CM, Angius A, Iacono WG, Schlessinger D, McGue M, Cucca F, Abecasis GR, Sanna S.

Eur J Hum Genet. 2015 Jul;23(7):975-83. doi: 10.1038/ejhg.2014.216. Epub 2014 Oct 8.

3.

Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies.

Hao K, Chudin E, McElwee J, Schadt EE.

BMC Genet. 2009 Jun 16;10:27. doi: 10.1186/1471-2156-10-27.

4.

Founder population-specific HapMap panel increases power in GWA studies through improved imputation accuracy and CNV tagging.

Surakka I, Kristiansson K, Anttila V, Inouye M, Barnes C, Moutsianas L, Salomaa V, Daly M, Palotie A, Peltonen L, Ripatti S.

Genome Res. 2010 Oct;20(10):1344-51. doi: 10.1101/gr.106534.110. Epub 2010 Sep 1.

5.

Imputation-based assessment of next generation rare exome variant arrays.

Martin AR, Tse G, Bustamante CD, Kenny EE.

Pac Symp Biocomput. 2014:241-52.

6.

Imputation across genotyping arrays for genome-wide association studies: assessment of bias and a correction strategy.

Johnson EO, Hancock DB, Levy JL, Gaddis NC, Saccone NL, Bierut LJ, Page GP.

Hum Genet. 2013 May;132(5):509-22. doi: 10.1007/s00439-013-1266-7. Epub 2013 Jan 22.

7.

Assessment of genotype imputation performance using 1000 Genomes in African American studies.

Hancock DB, Levy JL, Gaddis NC, Bierut LJ, Saccone NL, Page GP, Johnson EO.

PLoS One. 2012;7(11):e50610. doi: 10.1371/journal.pone.0050610. Epub 2012 Nov 30.

8.

Improved imputation quality of low-frequency and rare variants in European samples using the 'Genome of The Netherlands'.

Deelen P, Menelaou A, van Leeuwen EM, Kanterakis A, van Dijk F, Medina-Gomez C, Francioli LC, Hottenga JJ, Karssen LC, Estrada K, Kreiner-Møller E, Rivadeneira F, van Setten J, Gutierrez-Achury J, Westra HJ, Franke L, van Enckevort D, Dijkstra M, Byelas H, van Duijn CM; Genome of Netherlands Consortium, de Bakker PI, Wijmenga C, Swertz MA.

Eur J Hum Genet. 2014 Nov;22(11):1321-6. doi: 10.1038/ejhg.2014.19. Epub 2014 Jun 4.

9.

Effect of genome-wide genotyping and reference panels on rare variants imputation.

Zheng HF, Ladouceur M, Greenwood CM, Richards JB.

J Genet Genomics. 2012 Oct 20;39(10):545-50. doi: 10.1016/j.jgg.2012.07.002. Epub 2012 Jul 24.

PMID:
23089364
10.

Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture.

Zheng HF, Forgetta V, Hsu YH, Estrada K, Rosello-Diez A, Leo PJ, Dahia CL, Park-Min KH, Tobias JH, Kooperberg C, Kleinman A, Styrkarsdottir U, Liu CT, Uggla C, Evans DS, Nielson CM, Walter K, Pettersson-Kymmer U, McCarthy S, Eriksson J, Kwan T, Jhamai M, Trajanoska K, Memari Y, Min J, Huang J, Danecek P, Wilmot B, Li R, Chou WC, Mokry LE, Moayyeri A, Claussnitzer M, Cheng CH, Cheung W, Medina-Gómez C, Ge B, Chen SH, Choi K, Oei L, Fraser J, Kraaij R, Hibbs MA, Gregson CL, Paquette D, Hofman A, Wibom C, Tranah GJ, Marshall M, Gardiner BB, Cremin K, Auer P, Hsu L, Ring S, Tung JY, Thorleifsson G, Enneman AW, van Schoor NM, de Groot LC, van der Velde N, Melin B, Kemp JP, Christiansen C, Sayers A, Zhou Y, Calderari S, van Rooij J, Carlson C, Peters U, Berlivet S, Dostie J, Uitterlinden AG, Williams SR, Farber C, Grinberg D, LaCroix AZ, Haessler J, Chasman DI, Giulianini F, Rose LM, Ridker PM, Eisman JA, Nguyen TV, Center JR, Nogues X, Garcia-Giralt N, Launer LL, Gudnason V, Mellström D, Vandenput L, Amin N, van Duijn CM, Karlsson MK, Ljunggren Ö, Svensson O, Hallmans G, Rousseau F, Giroux S, Bussière J, Arp PP, Koromani F, Prince RL, Lewis JR, Langdahl BL, Hermann AP, Jensen JE, Kaptoge S, Khaw KT, Reeve J, Formosa MM, Xuereb-Anastasi A, Åkesson K, McGuigan FE, Garg G, Olmos JM, Zarrabeitia MT, Riancho JA, Ralston SH, Alonso N, Jiang X, Goltzman D, Pastinen T, Grundberg E, Gauguier D, Orwoll ES, Karasik D, Davey-Smith G; AOGC Consortium, Smith AV, Siggeirsdottir K, Harris TB, Zillikens MC, van Meurs JB, Thorsteinsdottir U, Maurano MT, Timpson NJ, Soranzo N, Durbin R, Wilson SG, Ntzani EE, Brown MA, Stefansson K, Hinds DA, Spector T, Cupples LA, Ohlsson C, Greenwood CM; UK10K Consortium, Jackson RD, Rowe DW, Loomis CA, Evans DM, Ackert-Bicknell CL, Joyner AL, Duncan EL, Kiel DP, Rivadeneira F, Richards JB.

Nature. 2015 Oct 1;526(7571):112-7. doi: 10.1038/nature14878. Epub 2015 Sep 14.

11.

Whole-exome imputation of sequence variants identified two novel alleles associated with adult body height in African Americans.

Du M, Auer PL, Jiao S, Haessler J, Altshuler D, Boerwinkle E, Carlson CS, Carty CL, Chen YD, Curtis K, Franceschini N, Hsu L, Jackson R, Lange LA, Lettre G, Monda KL; National Heart, Lung, and Blood Institute (NHLBI) GO Exome Sequencing Project, Nickerson DA, Reiner AP, Rich SS, Rosse SA, Rotter JI, Willer CJ, Wilson JG, North K, Kooperberg C, Heard-Costa N, Peters U.

Hum Mol Genet. 2014 Dec 15;23(24):6607-15. doi: 10.1093/hmg/ddu361. Epub 2014 Jul 15.

12.

PreCimp: Pre-collapsing imputation approach increases imputation accuracy of rare variants in terms of collapsed variables.

Kim YJ, Lee J, Kim BJ; T2D-Genes Consortium, Park T.

Genet Epidemiol. 2017 Jan;41(1):41-50. doi: 10.1002/gepi.22020. Epub 2016 Nov 10.

PMID:
27859580
13.

Accuracy of imputation to infer unobserved APOE epsilon alleles in genome-wide genotyping data.

Radmanesh F, Devan WJ, Anderson CD, Rosand J, Falcone GJ; Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Eur J Hum Genet. 2014 Oct;22(10):1239-42. doi: 10.1038/ejhg.2013.308. Epub 2014 Jan 22.

14.

The relationship between imputation error and statistical power in genetic association studies in diverse populations.

Huang L, Wang C, Rosenberg NA.

Am J Hum Genet. 2009 Nov;85(5):692-8. doi: 10.1016/j.ajhg.2009.09.017. Epub 2009 Oct 22.

15.

A generic coalescent-based framework for the selection of a reference panel for imputation.

Paşaniuc B, Avinery R, Gur T, Skibola CF, Bracci PM, Halperin E.

Genet Epidemiol. 2010 Dec;34(8):773-82. doi: 10.1002/gepi.20505.

16.

Genotype imputation of Metabochip SNPs using a study-specific reference panel of ~4,000 haplotypes in African Americans from the Women's Health Initiative.

Liu EY, Buyske S, Aragaki AK, Peters U, Boerwinkle E, Carlson C, Carty C, Crawford DC, Haessler J, Hindorff LA, Marchand LL, Manolio TA, Matise T, Wang W, Kooperberg C, North KE, Li Y.

Genet Epidemiol. 2012 Feb;36(2):107-17. doi: 10.1002/gepi.21603.

17.

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data.

Kim YJ, Lee J, Kim BJ; T2D-Genes Consortium, Park T.

BMC Genomics. 2015 Dec 29;16:1109. doi: 10.1186/s12864-015-2192-y.

18.

Imputation of low-frequency variants using the HapMap3 benefits from large, diverse reference sets.

Jostins L, Morley KI, Barrett JC.

Eur J Hum Genet. 2011 Jun;19(6):662-6. doi: 10.1038/ejhg.2011.10. Epub 2011 Mar 2.

19.

Molecular genetic studies of complex phenotypes.

Marian AJ.

Transl Res. 2012 Feb;159(2):64-79. doi: 10.1016/j.trsl.2011.08.001. Epub 2011 Aug 31. Review.

20.

Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip.

Spencer CC, Su Z, Donnelly P, Marchini J.

PLoS Genet. 2009 May;5(5):e1000477. doi: 10.1371/journal.pgen.1000477. Epub 2009 May 15.

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