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Items: 1 to 20 of 122

1.

A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals.

Clark TG, Campino SG, Anastasi E, Auburn S, Teo YY, Small K, Rockett KA, Kwiatkowski DP, Holmes CC.

Bioinformatics. 2010 Aug 15;26(16):1999-2003. doi: 10.1093/bioinformatics/btq327. Epub 2010 Jun 16.

2.

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.

3.

GLIDERS--a web-based search engine for genome-wide linkage disequilibrium between HapMap SNPs.

Lawrence R, Day-Williams AG, Mott R, Broxholme J, Cardon LR, Zeggini E.

BMC Bioinformatics. 2009 Oct 31;10:367. doi: 10.1186/1471-2105-10-367.

5.

Power-based, phase-informed selection of single nucleotide polymorphisms for disease association screens.

Saccone SF, Rice JP, Saccone NL.

Genet Epidemiol. 2006 Sep;30(6):459-70.

PMID:
16685721
6.

LD2SNPing: linkage disequilibrium plotter and RFLP enzyme mining for tag SNPs.

Chang HW, Chuang LY, Chang YJ, Cheng YH, Hung YC, Chen HC, Yang CH.

BMC Genet. 2009 Jun 6;10:26. doi: 10.1186/1471-2156-10-26.

7.

Similarity in recombination rate and linkage disequilibrium at CYP2C and CYP2D cytochrome P450 gene regions among Europeans indicates signs of selection and no advantage of using tagSNPs in population isolates.

Pimenoff VN, Laval G, Comas D, Palo JU, Gut I, Cann H, Excoffier L, Sajantila A.

Pharmacogenet Genomics. 2012 Dec;22(12):846-57. doi: 10.1097/FPC.0b013e32835a3a6d.

PMID:
23089684
8.
9.

Marker selection for genetic case-control association studies.

Pettersson FH, Anderson CA, Clarke GM, Barrett JC, Cardon LR, Morris AP, Zondervan KT.

Nat Protoc. 2009;4(5):743-52. doi: 10.1038/nprot.2009.38. Epub 2009 Apr 23.

10.

Extent and consistency of linkage disequilibrium and identification of DNA markers for production and egg quality traits in commercial layer chicken populations.

Abasht B, Sandford E, Arango J, Settar P, Fulton JE, O'Sullivan NP, Hassen A, Habier D, Fernando RL, Dekkers JC, Lamont SJ.

BMC Genomics. 2009 Jul 14;10 Suppl 2:S2. doi: 10.1186/1471-2164-10-S2-S2.

11.

Increasing power of genome-wide association studies by collecting additional single-nucleotide polymorphisms.

Kostem E, Lozano JA, Eskin E.

Genetics. 2011 Jun;188(2):449-60. doi: 10.1534/genetics.111.128595. Epub 2011 Apr 5.

12.
13.

varLD: a program for quantifying variation in linkage disequilibrium patterns between populations.

Ong RT, Teo YY.

Bioinformatics. 2010 May 1;26(9):1269-70. doi: 10.1093/bioinformatics/btq125. Epub 2010 Mar 22.

14.

Genome-wide selection of tag SNPs using multiple-marker correlation.

Hao K.

Bioinformatics. 2007 Dec 1;23(23):3178-84. Epub 2007 Nov 15.

15.

HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms.

Zhang K, Qin Z, Chen T, Liu JS, Waterman MS, Sun F.

Bioinformatics. 2005 Jan 1;21(1):131-4. Epub 2004 Aug 27.

16.

Bayesian estimates of linkage disequilibrium.

Sebastiani P, Abad-Grau MM.

BMC Genet. 2007 Jun 25;8:36.

17.
18.

An integrated approach to reduce the impact of minor allele frequency and linkage disequilibrium on variable importance measures for genome-wide data.

Walters R, Laurin C, Lubke GH.

Bioinformatics. 2012 Oct 15;28(20):2615-23. doi: 10.1093/bioinformatics/bts483. Epub 2012 Jul 30.

19.

Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies.

Hoggart CJ, Whittaker JC, De Iorio M, Balding DJ.

PLoS Genet. 2008 Jul 25;4(7):e1000130. doi: 10.1371/journal.pgen.1000130.

20.

The impact of SNP density on fine-scale patterns of linkage disequilibrium.

Ke X, Hunt S, Tapper W, Lawrence R, Stavrides G, Ghori J, Whittaker P, Collins A, Morris AP, Bentley D, Cardon LR, Deloukas P.

Hum Mol Genet. 2004 Mar 15;13(6):577-88. Epub 2004 Jan 20.

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