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Items: 1 to 20 of 81

1.

Fast pairwise IBD association testing in genome-wide association studies.

Han B, Kang EY, Raychaudhuri S, de Bakker PI, Eskin E.

Bioinformatics. 2014 Jan 15;30(2):206-13. doi: 10.1093/bioinformatics/btt609.

2.

Detecting rare variant associations by identity-by-descent mapping in case-control studies.

Browning SR, Thompson EA.

Genetics. 2012 Apr;190(4):1521-31. doi: 10.1534/genetics.111.136937.

3.

BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies.

Wan X, Yang C, Yang Q, Xue H, Fan X, Tang NL, Yu W.

Am J Hum Genet. 2010 Sep 10;87(3):325-40. doi: 10.1016/j.ajhg.2010.07.021.

4.

Relationship estimation from whole-genome sequence data.

Li H, Glusman G, Hu H, Shankaracharya, Caballero J, Hubley R, Witherspoon D, Guthery SL, Mauldin DE, Jorde LB, Hood L, Roach JC, Huff CD.

PLoS Genet. 2014 Jan 30;10(1):e1004144. doi: 10.1371/journal.pgen.1004144.

5.

DASH: a method for identical-by-descent haplotype mapping uncovers association with recent variation.

Gusev A, Kenny EE, Lowe JK, Salit J, Saxena R, Kathiresan S, Altshuler DM, Friedman JM, Breslow JL, Pe'er I.

Am J Hum Genet. 2011 Jun 10;88(6):706-17. doi: 10.1016/j.ajhg.2011.04.023.

6.

A fast, powerful method for detecting identity by descent.

Browning BL, Browning SR.

Am J Hum Genet. 2011 Feb 11;88(2):173-82. doi: 10.1016/j.ajhg.2011.01.010.

7.

Using identity by descent estimation with dense genotype data to detect positive selection.

Han L, Abney M.

Eur J Hum Genet. 2013 Feb;21(2):205-11. doi: 10.1038/ejhg.2012.148.

8.

A method for detecting IBD regions simultaneously in multiple individuals--with applications to disease genetics.

Moltke I, Albrechtsen A, Hansen TV, Nielsen FC, Nielsen R.

Genome Res. 2011 Jul;21(7):1168-80. doi: 10.1101/gr.115360.110.

9.

Efficient clustering of identity-by-descent between multiple individuals.

Qian Y, Browning BL, Browning SR.

Bioinformatics. 2014 Apr 1;30(7):915-22. doi: 10.1093/bioinformatics/btt734.

10.

Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping.

Bercovici S, Meek C, Wexler Y, Geiger D.

Bioinformatics. 2010 Jun 15;26(12):i175-82. doi: 10.1093/bioinformatics/btq204.

12.

Predicting the number and sizes of IBD regions among family members and evaluating the family size requirement for linkage studies.

Yang W, Wang Z, Wang L, Sham PC, Huang P, Lau YL.

Eur J Hum Genet. 2008 Dec;16(12):1535-43. doi: 10.1038/ejhg.2008.116.

13.

Missingness in the T1DGC MHC fine-mapping SNP data: association with HLA genotype and potential influence on genetic association studies.

James I, McKinnon E, Gaudieri S, Morahan G; Diabetes Genetics Consortium..

Diabetes Obes Metab. 2009 Feb;11 Suppl 1:101-7. doi: 10.1111/j.1463-1326.2008.01010.x.

14.

PBOOST: a GPU-based tool for parallel permutation tests in genome-wide association studies.

Yang G, Jiang W, Yang Q, Yu W.

Bioinformatics. 2015 May 1;31(9):1460-2. doi: 10.1093/bioinformatics/btu840.

PMID:
25535244
15.

On the simultaneous association analysis of large genomic regions: a massive multi-locus association test.

Qiao D, Cho MH, Fier H, Bakke PS, Gulsvik A, Silverman EK, Lange C.

Bioinformatics. 2014 Jan 15;30(2):157-64. doi: 10.1093/bioinformatics/btt654.

16.

Relatedness mapping and tracts of relatedness for genome-wide data in the presence of linkage disequilibrium.

Albrechtsen A, Sand Korneliussen T, Moltke I, van Overseem Hansen T, Nielsen FC, Nielsen R.

Genet Epidemiol. 2009 Apr;33(3):266-74. doi: 10.1002/gepi.20378.

PMID:
19025785
17.
18.

PIGS: improved estimates of identity-by-descent probabilities by probabilistic IBD graph sampling.

Park DS, Baran Y, Hormozdiari F, Eng C, Torgerson DG, Burchard EG, Zaitlen N.

BMC Bioinformatics. 2015;16 Suppl 5:S9. doi: 10.1186/1471-2105-16-S5-S9.

19.

Estimating the degree of identity by descent in consanguineous couples.

Carr IM, Markham SA, Pena SD.

Hum Mutat. 2011 Dec;32(12):1350-8. doi: 10.1002/humu.21584.

PMID:
21901788
20.

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