Strategies for conditional two-locus nonparametric linkage analysis
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Strategies for conditional two-locus nonparametric linkage analysis. / Ängquist, Lars; Hössjer, Ola; Groop, Leif.
I: Human Heredity, Bind 66, Nr. 3, 01.07.2008, s. 138-156.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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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 -
ID: 203374273