TY - JOUR

T1 - Strategies for conditional two-locus nonparametric linkage analysis

AU - Ängquist, Lars

AU - Hössjer, Ola

AU - Groop, Leif

PY - 2008/7/1

Y1 - 2008/7/1

N2 - In this article we deal with two-locus nonparametric linkage (NPL) analysis, mainly in the context of conditional analysis. This means that one incorporates single-locus analysis information through conditioning when performing a two-locus analysis. Here we describe different strategies for using this approach. Cox et al. [Nat Genet 1999;21:213-215] implemented this as follows: (i) Calculate the one-locus NPL process over the included genome region(s). (ii) Weight the individual pedigree NPL scores using a weighting function depending on the NPL scores for the corresponding pedigrees at specific conditioning loci. We generalize this by conditioning with respect to the inheritance vector rather than the NPL score and by separating between the case of known (predefined) and unknown (estimated) conditioning loci. In the latter case we choose conditioning locus, or loci, according to predefined criteria. The most general approach results in a random number of selected loci, depending on the results from the previous one-locus analysis. Major topics in this article include discussions on optimal score functions with respect to the noncentrality parameter (NCP), and how to calculate adequate p values and perform power calculations. We also discuss issues related to multiple tests which arise from the two-step procedure with several conditioning loci as well as from the genome-wide tests.

AB - In this article we deal with two-locus nonparametric linkage (NPL) analysis, mainly in the context of conditional analysis. This means that one incorporates single-locus analysis information through conditioning when performing a two-locus analysis. Here we describe different strategies for using this approach. Cox et al. [Nat Genet 1999;21:213-215] implemented this as follows: (i) Calculate the one-locus NPL process over the included genome region(s). (ii) Weight the individual pedigree NPL scores using a weighting function depending on the NPL scores for the corresponding pedigrees at specific conditioning loci. We generalize this by conditioning with respect to the inheritance vector rather than the NPL score and by separating between the case of known (predefined) and unknown (estimated) conditioning loci. In the latter case we choose conditioning locus, or loci, according to predefined criteria. The most general approach results in a random number of selected loci, depending on the results from the previous one-locus analysis. Major topics in this article include discussions on optimal score functions with respect to the noncentrality parameter (NCP), and how to calculate adequate p values and perform power calculations. We also discuss issues related to multiple tests which arise from the two-step procedure with several conditioning loci as well as from the genome-wide tests.

KW - Conditional linkage analysis

KW - Conditioning loci

KW - Genome-wide significance and power calculations

KW - Monte Carlo simulation

KW - Noncentrality parameter

KW - Nonparametric linkage analysis

KW - ROC curves

KW - Score functions

KW - Two-locus linkage analysis

KW - Two-step procedure

UR - http://www.scopus.com/inward/record.url?scp=46249125905&partnerID=8YFLogxK

U2 - 10.1159/000126049

DO - 10.1159/000126049

M3 - Journal article

C2 - 18418001

AN - SCOPUS:46249125905

VL - 66

SP - 138

EP - 156

JO - Human Heredity

JF - Human Heredity

SN - 0001-5652

IS - 3

ER -