How can maximum likelihood methods reveal candidate gene effects on a quantitative trait?

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How can maximum likelihood methods reveal candidate gene effects on a quantitative trait? is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1002/GEPI.1370120643
P698PubMed publication ID8788010

P50authorLaurent AbelQ30503755
Florence DemenaisQ56420237
Maria MartinezQ56827527
P2093author name stringM. Martinez
P2860cites workStrategies for multilocus linkage analysis in humansQ27860521
Equivalence of the mixed and regressive models for genetic analysis. I. Continuous traitsQ43487802
The use of measured genotype information in the analysis of quantitative phenotypes in man. I. Models and analytical methods.Q52642402
On the statistical determination of major gene mechanisms in continuous human traits: regressive models.Q52690588
P433issue6
P921main subjectquantitative traitQ112670498
P304page(s)789-794
P577publication date1995-01-01
P1433published inGenetic EpidemiologyQ5532864
P1476titleHow can maximum likelihood methods reveal candidate gene effects on a quantitative trait?
P478volume12

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cites work (P2860)
Q77496218Comparison of likelihood approaches for combined segregation and linkage analysis of a complex disease and a candidate gene marker under different ascertainment schemes
Q35250050Detection of gene-environment interactions in joint segregation and linkage analysis
Q56893651Detection of putative functional angiotensinogen (AGT) gene variants controlling plasma AGT levels by combined segregation-linkage analysis
Q52204062Dissecting the loci controlling fetal haemoglobin production on chromosomes 11p and 6q by the regressive approach.
Q56893780Indication of linkage of serum IgE levels to the interleukin-4 gene and exclusion of the contribution of the (-590 C to T) interleukin-4 promoter polymorphism to IgE variation
Q56893664Regressive threshold model for familial analysis of complex diseases with variable age of onset

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