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Likelihood Analysis (likelihood + analysis)
Kinds of Likelihood Analysis Selected AbstractsLikelihood Analysis for the Ratio of Means of Two Independent Log-Normal DistributionsBIOMETRICS, Issue 2 2002Jianrong Wu Summary. Existing methods for comparing the means of two independent skewed log-normal distributions do not perform well in a range of small-sample settings such as a small-sample bioavailability study. In this article, we propose two likelihood-based approaches,the signed log-likelihood ratio statistic and modified signed log-likelihood ratio statistic,for inference about the ratio of means of two independent log-normal distributions. More specifically, we focus on obtaining p -values for testing the equality of means and also constructing confidence intervals for the ratio of means. The performance of the proposed methods is assessed through simulation studies that show that the modified signed log-likelihood ratio statistic is nearly an exact approach even for very small samples. The methods are also applied to two real-life examples. [source] Likelihood analysis of joint marginal and conditional models for longitudinal categorical dataTHE CANADIAN JOURNAL OF STATISTICS, Issue 2 2009Baojiang Chen MSC 2000: Primary 62H12; secondary 62F10 Abstract The authors develop a Markov model for the analysis of longitudinal categorical data which facilitates modelling both marginal and conditional structures. A likelihood formulation is employed for inference, so the resulting estimators enjoy the optimal properties such as efficiency and consistency, and remain consistent when data are missing at random. Simulation studies demonstrate that the proposed method performs well under a variety of situations. Application to data from a smoking prevention study illustrates the utility of the model and interpretation of covariate effects. The Canadian Journal of Statistics © 2009 Statistical Society of Canada Les auteurs développent un modèle de Markov pour l'analyse de données catégorielles longitudinales facilitant la représentation des structures marginales et conditionnelles. L'inférence est basée sur une fonction de vraisemblance afin d'obtenir des estimateurs efficaces, cohérents et qui le demeurent lorsqu'il y a des données manquantes au hasard. Des études de simulation montrent que la méthode proposée se comporte bien dans les différents scénarios considérés. L'application à des données provenant d'une étude sur la lutte contre le tabagisme illustre bien l'utilité de ce modèle et permet une interprétation des effets des covariables. La revue canadienne de statistique © 2009 Société statistique du Canada [source] Robust support for tardigrade clades and their ages from three protein-coding nuclear genesINVERTEBRATE BIOLOGY, Issue 2 2004Jerome C. Regier Abstract. Coding sequences (5,334 nt total) from elongation factor-1,, elongation factor-2, and the largest subunit of RNA polymerase II were determined for 6 species of Tardigrada, 2 of Arthropoda, and 2 of Onychophora. Parsimony and likelihood analyses of nucleotides and amino acids yielded strong support for Tardigrada and all internal nodes (i.e., 100% bootstrap support for Tardigrada, Eutardigrada, Parachela, Hypsibiidae, and Macrobiotidae). Results are in agreement with morphology and an earlier molecular study based on analysis of 18S ribosomal sequences. Divergence times have been estimated from amino acid sequence data using an empirical Bayesian statistical approach, which does not assume a strict molecular clock. Divergence time estimates are pre-Vendian for Tardigrada/Arthropoda, Vendian or earlier for Eutardigrada/Heterotardigrada, Silurian to Ordovician for Parachela/Apochela, Permian to Carboniferous for Hypsibiidae and Macrobiotidae, and Mesozoic for Isohypsibius/Thulinia (both within Hypsibiidae) and Macrobiotus/Richtersius (both within Macrobiotidae). [source] Parallel evolution of larval morphology and habitat in the snail-killing fly genus TetanoceraJOURNAL OF EVOLUTIONARY BIOLOGY, Issue 5 2006E. G. CHAPMAN Abstract In this study, we sequenced one nuclear and three mitochondrial DNA loci to construct a robust estimate of phylogeny for all available species of Tetanocera. Character optimizations suggested that aquatic habitat was the ancestral condition for Tetanocera larvae, and that there were at least three parallel transitions to terrestrial habitat, with one reversal. Maximum likelihood analyses of character state transformations showed significant correlations between habitat transitions and changes in four larval morphological characteristics (cuticular pigmentation and three characters associated with the posterior spiracular disc). We provide evidence that phylogenetic niche conservatism has been responsible for the maintenance of aquatic-associated larval morphological character states, and that concerted convergence and/or gene linkage was responsible for parallel morphological changes that were derived in conjunction with habitat transitions. These habitat,morphology associations were consistent with the action of natural selection in facilitating the morphological changes that occurred during parallel aquatic to terrestrial habitat transitions in Tetanocera. [source] SYSTEMATICS OF GRACILARIOPSIS (GRACILARIALES, RHODOPHYTA) BASED ON rbcL SEQUENCE ANALYSES AND MORPHOLOGICAL EVIDENCE,JOURNAL OF PHYCOLOGY, Issue 1 2003Carlos Frederico D. Gurgel A phylogeny has been inferred from parsimony and likelihood analyses of plastid rbcL DNA sequences for seven recognized and six undescribed species of Gracilariopsis (Gp.) (Gracilariales, Rhodophyta). New descriptions and illustrations of cystocarp morphology are provided for four Gracilariopsis species from North and South America. The generitype, Gp. sjoestedtii (Kylin) Dawson, is reinstated to include plants distributed from British Columbia to Pacific Baja California, and the name is corrected to Gp. andersonii (Grunow) Dawson. Gracilariopsis lemaneiformis (Bory) Dawson, Acleto et Foldvik is shown not to have a worldwide distribution but to be restricted to the vicinity of Peru. Gracilariopsis costaricensis is recognized with the provision that it may prove to be conspecific with Gp. lemaneiformis. Gracilariopsis "lemaneiformis" from North and South Carolina is described as a new species, Gp. carolinensis Liao et Hommersand sp. nov. Gracilariopsis longissima (Gmelin) Steentoft, Irvine et Farnham from Western Europe and the Mediterranean Sea and Gp. tenuifrons (Bird et Oliveira) Fredericq et Hommersand from the Ca-ribbean Sea and Brazil are recognized. Entities that have been referred to Gp. "lemaneiformis" from China and Japan constitute an undescribed species that is related to Gp. heteroclada Zhang et Xia. An invasive species from the Gulf of California, Mexico, and South Australia that has been assigned to Gp. "lemaneiformis" is resolved in a clade that includes Gp. longissima. Four undescribed species are included in the molecular analyses. The systematics of Gracilariopsis is discussed in the light of the morphological and molecular evidence. [source] Phylogeography and speciation of colour morphs in the colonial ascidian Pseudodistoma crucigasterMOLECULAR ECOLOGY, Issue 10 2004I. TARJUELO Abstract Variation in pigmentation is common in marine invertebrates, although few studies have shown the existence of genetic differentiation of chromatic forms in these organisms. We studied the genetic structure of a colonial ascidian with populations of different colour morphs in the northwestern Mediterranean. A fragment of the c oxidase subunit 1 (COI) mitochondrial gene was sequenced in seven populations of Pseudodistoma crucigaster belonging to three different colour morphs (orange, yellow and grey). Maximum likelihood analyses showed two well-supported clades separating the orange morph from the yellow-grey morphotypes. Genetic divergence between these clades was 2.12%, and ,ST values between populations of the two clades were high (average 0.936), pointing to genetic isolation. Nested clade and coalescence analyses suggest that a past fragmentation event may explain the phylogeographical origin of these two clades. Non-neutral mtDNA evolution is observed in our data when comparing the two clades, showing a significant excess of nonsynonymous polymorphism within the yellow,grey morphotype using the McDonald,Kreitman test, which is interpreted as further support of reproductive isolation. We conclude that the two clades might represent separate species. We compare the population genetic differentiation found with that estimated for other colonial and solitary ascidian species, and relate it to larval dispersal capabilities and other life-history traits. [source] Their Day in the Sun: molecular phylogenetics and origin of photosymbiosis in the ,other' group of photosymbiotic marine bivalves (Cardiidae: Fraginae)BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY, Issue 2 2009LISA KIRKENDALE The subfamily Fraginae (Cardiidae) is a morphologically diverse group of small-bodied marine clams inhabiting shallow seas worldwide. Like the exclusively photosymbiotic giant clams (Cardiidae: Tridacninae), some fragines are known to host zooxanthellae photosymbionts. However, surveys to widely determine photosymbiotic status and the lack of a comprehensive phylogeny have hindered attempts to track the evolution of photosymbiosis in the group. Worldwide sampling of all fragine genera and subgenera with phylogenetic reconstructions based on four gene regions [nuclear (28S) and mtDNA (16S, cytochrome oxidase I, cytochrome b)] does not support a monophyletic Fraginae. Sampled taxa form four restructured clades: (1) the ,Fragum' group, (2) the ,Trigoniocardia' and ,Ctenocardia' groups, (3) the ,Parvicardium' group and (4) the ,Papillicardium' group. Maximum likelihood analyses strongly support a clade of European cardiids uniting species from three subfamilies. Live examination of > 50% of species reveals that less than half of derived genera and subgenera host photosymbionts, supporting a single and relatively late origin of photosymbiosis in the Fraginae. The evolutionary implications for a small and little modified earliest diverging photosymbiotic lineage are discussed. © 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 97, 448,465. [source] Significance testing of synergistic/antagonistic, dose level-dependent, or dose ratio-dependent effects in mixture dose-response analysisENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 10 2005Martijs J. Jonker Abstract In ecotoxicology, the state of the art for effect assessment of chemical mixtures is through multiple dose,response analysis of single compounds and their combinations. Investigating whether such data deviate from the reference models of concentration addition and/or independent action to identify overall synergism or antagonism is becoming routine. However, recent data show that more complex deviation patterns, such as dose ratio,dependent deviation and dose level,dependent deviation, need to be addressed. For concentration addition, methods to detect such deviation patterns exist, but they are stand-alone methods developed separately in literature, and conclusions derived from these analyses are therefore difficult to compare. For independent action, hardly any methods to detect such deviations from this reference model exist. This paper describes how these well-established mixture toxicity principles have been incorporated in a coherent data analysis procedure enabling detection and quantification of dose level,and dose ratio,specific synergism or antagonism from both the concentration addition and the independent action models. Significance testing of which deviation pattern describes the data best is carried out through maximum likelihood analysis. This analysis procedure is demonstrated through various data sets, and its applicability and limitations in mixture research are discussed. [source] WHEN VICARS MEET: A NARROW CONTACT ZONE BETWEEN MORPHOLOGICALLY CRYPTIC PHYLOGEOGRAPHIC LINEAGES OF THE RAINFOREST SKINK, CARLIA RUBRIGULARISEVOLUTION, Issue 7 2004Ben L. Phillips Abstract Phylogeographic analyses of the fauna of the Australian wet tropics rainforest have provided strong evidence for long-term isolation of populations among allopatric refugia, yet typically there is no corresponding divergence in morphology. This system provides an opportunity to examine the consequences of geographic isolation, independent of morphological divergence, and thus to assess the broader significance of historical subdivisions revealed through mitochondrial DNA phylogeography. We have located and characterized a zone of secondary contact between two long isolated (mtDNA divergence > 15%) lineages of the skink Carlia rubrigularis using one mitochondrial and eight nuclear (two intron, six microsatellite) markers. This revealed a remarkably narrow (width<3 km) hybrid zone with substantial linkage disequilibrium and strong deficits of heterozygotes at two of three nuclear loci with diagnostic alleles. Cline centers were coincident across loci. Using a novel form of likelihood analysis, we were unable to distinguish between sigmoidal and stepped cline shapes except at one nuclear locus for which the latter was inferred. Given estimated dispersal rates of 90,133 m X gen,1/2 and assuming equilibrium, the observed cline widths suggest effective selection against heterozygotes of at least 22,49% and possibly as high as 70%. These observations reveal substantial postmating isolation, although the absence of consistent deviations from Hardy-Weinberg equilibrium at diagnostic loci suggests that there is little accompanying premating isolation. The tight geographic correspondence between transitions in mtDNA and those for nuclear genes and corresponding evidence for selection against hybrids indicates that these morphologically cryptic phylogroups could be considered as incipient species. Nonetheless, we caution against the use of mtDNA phylogeography as a sole criterion for defining species boundaries. [source] Determination of the inheritance pattern of hyperthelia in cattle by maximum likelihood analysis 1JOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 6 2000M. Brka Summary A previously published data-set with observations on supernumerary teats (hyperthelia) in dual-purpose Simmental was reanalysed by maximum-likelihood. The data comprised 537 unrelated animals and 614 members of 27 paternal half-sib families with known phenotype of each sire. The frequency of hyperthelia was 58% in unrelated animals, 51% in families with unaffected sire, and 73% in families with affected sires. Six different cases of single-gene inheritance were considered. The highest log-likelihood was obtained for additive inheritance and for a recessive pattern with 100% penetrance for recessive homozygotes and 32% for both other genotypes. Estimates for the gene frequency of the favourable allele were 0.34 and 0.29, respectively. Simple dominance or recessiveness with full or incomplete penetrance could be excluded. The possibility of finding paternal half-sib families with a heterozygous sire as a resource for a mapping experiment seem to be good in German Simmental. Zusammenfassung Untersuchung des Erbganges für Hyperthelie beim Rind mittels Maximum-Likelihood-Analyse Schon früher veröffentliche Daten mit Beobachtungen zum Auftreten überzähliger Zitzen (Hyperthelie) bei Fleckviehtieren wurden einer Maximum-Likelihood-Analyse unterzogen. Das Material bestand aus 537 unverwandten Tieren und 614 Tieren, die aus 27 verschiedenen väterlichen Halbgeschwistergruppen stammten, wobei der Phänotyp des Vaters jeweils bekannt war. Die relative Häufigkeit überzähliger Zitzen betrug 58% bei unverwandten Tieren, 51% bei Nachkommen von nicht betroffenen Vätern und 73% bei Nachkommen von Vätern, die selbst überzählige Zitzen aufwiesen. Sechs verschiedene Möglichkeiten monogener Vererbung wurden untersucht. Die höchsten Werte für die log-likelihood ergaben sich für einen additiven Erbgang sowie für eine Variante mit 100% Penetranz für die rezessiv Homozygoten und jeweils 32% Penetranz für die beiden anderen Genotypen. Für das erwünschte Allel wurde in beiden Varianten eine ähnliche Frequenz von 34% bzw. 29% geschätzt. Einfache dominante oder rezessive Erbgänge, auch mit unvollständiger Penetranz, konnten ausgeschlossen werden. Die Aussicht, für Kartierungsexperimente geeignete väterlichen Halbgeschwisterfamilien zu finden, scheint für die Rasse Fleckvieh günstig zu sein. [source] Cryptic differentiation and geographic variation in genetic diversity of Hall's Babbler Pomatostomus halliJOURNAL OF AVIAN BIOLOGY, Issue 2 2001Grant I. Miura Sequence variation was examined in domain I of the mitochondrial control region in three Queensland populations of Hall's Babbler Pomatostomus halli, a geographically restricted, monotypic songbird in eastern Australia. Surprisingly, we found that domain I sequences were strongly differentiated into two major clades differing by 3.29%. These two clades exhibited nearly complete geographic concordance with northern and southern populations, except for two haplotypes which were sampled in the north of the range but were phylogenetically allied to the southern clade. We also found a seven-fold higher level of genetic diversity in the northern than in the southern populations. Neutrality and molecular clock tests suggested that selection or differences in substitution rates were not responsible for this difference in diversity. However, a maximum likelihood analysis of gene flow between the north and south suggested that the difference in diversity could be due to both greater population size in the north and asymmetric gene flow dominated by south to north dispersal events. A likelihood ratio test rejected a model in which population sizes were equal and rates of gene flow symmetric, and came close to rejecting a model in which only population sizes were constrained to be equal. These results suggest that different population sizes and asymmetric gene flow could be a major source of differences in genetic variation between populations of Hall's Babbler, although ecological and biogeographic causes for these differences are obscure. [source] A multilocus study of pine grosbeak phylogeography supports the pattern of greater intercontinental divergence in Holarctic boreal forest birds than in birds inhabiting other high-latitude habitatsJOURNAL OF BIOGEOGRAPHY, Issue 4 2010Sergei V. Drovetski Abstract Aim, Boreal forest bird species appear to be divided into lineages endemic to each northern continent, in contrast to Holarctic species living in open habitats. For example, the three-toed woodpecker (Picoides tridactylus) and the winter wren (Troglodytes troglodytes) have divergent Nearctic and Palaearctic mitochondrial DNA clades. Furthermore, in these species, the next closest relative of the Nearctic/Palaearctic sister lineages is the Nearctic clade, suggesting that the Palaearctic may have been colonized from the Nearctic. The aim of this study is to test this pattern of intercontinental divergence and colonization in another Holarctic boreal forest resident , the pine grosbeak (Pinicola enucleator). Location, The Holarctic. Methods, We sequenced the mitochondrial ND2 gene and Z -specific intron 9 of the ACO1 gene for 74 pine grosbeaks collected across the Holarctic. The sequences were used to reconstruct the phylogeographical history of this species using maximum likelihood analysis. Results, We discovered two distinct mitochondrial and Z -specific lineages in the Nearctic and one in the Palaearctic. The two Nearctic mtDNA lineages, one in the northern boreal forest and one in south-western mountain forest, were more closely related to each other than either was to the Palaearctic clade. Two Nearctic Z-chromosome clades were sympatric in the boreal and south-western mountain forests. Unlike the topology of the mtDNA tree, the relationship among the Z-chromosome clades was the same as in the three-toed woodpecker and winter wren [Nearctic (Nearctic, Palaearctic)]. The Palaearctic Z-chromosome clade had much lower genetic diversity and a single-peak mismatch distribution with a mean < 25% of that for either Nearctic region, both of which had ragged mismatch distributions. Main conclusions, Our data suggest that, similar to the other boreal forest species, the pine grosbeak has divergent lineages in each northern continent and could have colonized the Palaearctic from the Nearctic. Compared with many Holarctic birds inhabiting open habitats, boreal forest species appear to be more differentiated, possibly because the boreal forests of the Nearctic and Palaearctic have been isolated since the Pliocene (3.5 Ma). [source] Biogeography of Plagiochila (Hepaticae): natural species groups span several floristic kingdomsJOURNAL OF BIOGEOGRAPHY, Issue 7 2003Henk Groth Abstract Aim This paper presents a synthesis of our recent results regarding the biogeography of Plagiochila using a molecular approach, and documents intercontinental ranges within this largest genus of the hepatics. Methods A maximum likelihood analysis of sixty-one nrITS sequences of Plagiochila was performed and the molecular topology obtained was compared with morphological, phytochemical and geographical data. Results Our molecular data set allowed the identification of eleven Plagiochila sections, the majority of which cover at least two floristic kingdoms. Seven sections have species in Europe (sect. Arrectae, Carringtoniae, Fuscoluteae, Glaucescentes, Plagiochila, Rutilantes, Vagae). Plagiochila species from Atlantic Europe are usually close to or conspecific with neotropical taxa, whereas species widespread in Europe are closely related to Asian ones and not to those in the Neotropics. Plagiochila sect. Arrectae represents a neotropical , Atlantic European clade. The section is not closely related , as has often been suggested , to the morphologically similar sect. Zonatae from Asia and western North America. Sequence data show that the African P. integerrima and the neotropical P. subplana are members of the Asian sect. Cucullatae (sect. Ciliatae, syn. nov.), which becomes pantropical in distribution. An ITS sequence of P. boryana from Uganda confirms the Afro-American range of the primarily neotropical sect. Hylacoetes. Similarities in sporophyte morphology between the sect. Cucullatae and sect. Hylacoetes are the result of parallel evolution. Main conclusions Our results indicate that intercontinental ranges at section and species level are common in Plagiochila. Carl's (1931) subdivision of Plagiochila into sections restricted to one floristic kingdom is outdated. Biogeographical patterns in Plagiochila are not dissimilar to those of other groups of bryophytes but elucidation of the geographical ranges of the taxa requires a molecular approach. Contrary to earlier belief, most Plagiochila species from Atlantic Europe do not have close relatives in Asia but are conspecific with or closely related to species from tropical America. [source] Pseudomartingale estimating equations for modulated renewal process modelsJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 1 2009Fengchang Lin Summary., We adapt martingale estimating equations based on gap time information to a general intensity model for a single realization of a modulated renewal process. The consistency and asymptotic normality of the estimators is proved under ergodicity conditions. Previous work has considered either parametric likelihood analysis or semiparametric multiplicative models using partial likelihood. The framework is generally applicable to semiparametric and parametric models, including additive and multiplicative specifications, and periodic models. It facilitates a semiparametric extension of a popular parametric earthquake model. Simulations and empirical analyses of Taiwanese earthquake sequences illustrate the methodology's practical utility. [source] Direct parametric inference for the cumulative incidence functionJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 2 2006Jong-Hyeon Jeong Summary., In survival data that are collected from phase III clinical trials on breast cancer, a patient may experience more than one event, including recurrence of the original cancer, new primary cancer and death. Radiation oncologists are often interested in comparing patterns of local or regional recurrences alone as first events to identify a subgroup of patients who need to be treated by radiation therapy after surgery. The cumulative incidence function provides estimates of the cumulative probability of locoregional recurrences in the presence of other competing events. A simple version of the Gompertz distribution is proposed to parameterize the cumulative incidence function directly. The model interpretation for the cumulative incidence function is more natural than it is with the usual cause-specific hazard parameterization. Maximum likelihood analysis is used to estimate simultaneously parametric models for cumulative incidence functions of all causes. The parametric cumulative incidence approach is applied to a data set from the National Surgical Adjuvant Breast and Bowel Project and compared with analyses that are based on parametric cause-specific hazard models and nonparametric cumulative incidence estimation. [source] A circular statistical method for extracting rotation measuresMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 2 2001S. Sarala We propose a new method for the extraction of rotation measures from spectral polarization data. The method is based on maximum likelihood analysis and takes into account the circular nature of the polarization data. The method is unbiased and statistically more efficient than the standard ,2 procedure. We also find that the method is computationally much more convenient than the standard ,2 procedure if the number of data points is very large. We find that for most sources the method gives results very close to the standard ,2 minimization procedure. We give results for all the cases for which the method gives significantly different results from ,2 minimization. We also make a ,3 fit to the data in order to extract non-Faraday rotation behaviour for those sources for which a large number of data points are available. [source] Comparison of the ENEAR peculiar velocities with the PSCz gravity fieldMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 3 2001Adi Nusser We present a comparison between the peculiar velocity field measured from the ENEAR all-sky Dn,, catalogue and that derived from the galaxy distribution of the IRAS Point Source Catalog Redshift Survey (PSCz). The analysis is based on a modal expansion of these data in redshift space by means of spherical harmonics and Bessel functions. The effective smoothing scale of the expansion is almost linear with redshift reaching 1500 km s,1 at 3000 km s,1. The general flow patterns in the filtered ENEAR and PSCz velocity fields agree well within 6000 km s,1, assuming a linear biasing relation between the mass and the PSCz galaxies. The comparison allows us to determine the parameter where , is the cosmological density parameter and b is the linear biasing factor. A likelihood analysis of the ENEAR and PSCz modes yields in good agreement with values obtained from Tully,Fisher surveys. [source] Morphology, Phylogeny, and Diversity of Trichonympha (Parabasalia: Hypermastigida) of the Wood-Feeding Cockroach Cryptocercus punctulatusTHE JOURNAL OF EUKARYOTIC MICROBIOLOGY, Issue 4 2009KEVIN J. CARPENTER ABSTRACT. Trichonympha is one of the most complex and visually striking of the hypermastigote parabasalids,a group of anaerobic flagellates found exclusively in hindguts of lower termites and the wood-feeding cockroach Cryptocercus,but it is one of only two genera common to both groups of insects. We investigated Trichonympha of Cryptocercus using light and electron microscopy (scanning and transmission), as well as molecular phylogeny, to gain a better understanding of its morphology, diversity, and evolution. Microscopy reveals numerous new features, such as previously undetected bacterial surface symbionts, adhesion of post-rostral flagella, and a distinctive frilled operculum. We also sequenced small subunit rRNA gene from manually isolated species, and carried out an environmental polymerase chain reaction (PCR) survey of Trichonympha diversity, all of which strongly supports monophyly of Trichonympha from Cryptocercus to the exclusion of those sampled from termites. Bayesian and distance methods support a relationship between Trichonympha species from termites and Cryptocercus, although likelihood analysis allies the latter with Eucomonymphidae. A monophyletic Trichonympha is of great interest because recent evidence supports a sister relationship between Cryptocercus and termites, suggesting Trichonympha predates the Cryptocercus- termite divergence. The monophyly of symbiotic bacteria of Trichonympha raises the intriguing possibility of three-way co-speciation among bacteria, Trichonympha, and insect hosts. [source] Alternative Oxidase (AOX) Genes of African Trypanosomes: Phylogeny and Evolution of AOX and Plastid Terminal Oxidase FamiliesTHE JOURNAL OF EUKARYOTIC MICROBIOLOGY, Issue 4 2005TAKASHI SUZUKI Abstract. To clarify evolution and phylogenetic relationships of trypanosome alternative oxidase (AOX) molecules, AOX genes (cDNAs) of the African trypanosomes, Trypanosoma congolense and Trypanosoma evansi, were cloned by PCR. Both AOXs possess conserved consensus motifs (-E-, -EXXH-). The putative amino acid sequence of the AOX of T. evansi was exactly the same as that of T. brucei. A protein phylogeny of trypanosome AOXs revealed that three genetically and pathogenically distinct strains of T. congolense are closely related to each other. When all known AOX sequences collected from current databases were analyzed, the common ancestor of these three Trypanosoma species shared a sister-group position to T. brucei/T. evansi. Monophyly of Trypanosoma spp. was clearly supported (100% bootstrap value) with Trypanosoma vivax placed at the most basal position of the Trypanosoma clade. Monophyly of other eukaryotic lineages, terrestrial plants + red algae, Metazoa, diatoms, Alveolata, oomycetes, green algae, and Fungi, was reconstructed in the best AOX tree obtained from maximum likelihood analysis, although some of these clades were not strongly supported. The terrestrial plants + red algae clade showed the closest affinity with an ,-proteobacterium, Novosphingobium aromaticivorans, and the common ancestor of these lineages, was separated from other eukaryotes. Although the root of the AOX subtree was not clearly determined, subsequent phylogenetic analysis of the composite tree for AOX and plastid terminal oxidase (PTOX) demonstrated that PTOX and related cyanobacterial sequences are of a monophyletic origin and their common ancestor is linked to AOX sequences. [source] There are High Levels of Functional and Genetic Diversity in Oxyrrhis marinaTHE JOURNAL OF EUKARYOTIC MICROBIOLOGY, Issue 3 2005CHRIS D. LOWE Abstract. Oxyrrhis marina, a widely distributed marine protist, is used to model heterotrophic flagellate responses in microbial food webs. Although clonal variability occurs in protists, assessments of intraspecific diversity are rare; such assessments are critical, particularly where species are used as models in ecological studies. To address the extent of intraspecific variation within O. marina, we assessed diversity among 11 strains using 5.8S rDNA and ITS sequences. The 5.8S rDNA and ITS regions revealed high divergence between strains: 63.1% between the most diverse. To compare O. marina diversity relative to other alveolates, 18S rDNA sequences for five strains were analysed with sequences from representatives of the major alveolate groups. 18S rDNA also revealed high divergence in O. marina. Additionally, consistent with phylogenies based on protein coding genes, maximum likelihood analysis indicated that O. marina was monophyletic and ancestral to the dinoflagellates. To assess ecophysiological differences, growth rates of seven O. marina strains were measured at 10 salinities (10,55,). Two salinity responses occurred: one group achieved highest growth rates at high salinities; the other grew best at low salinities. There was no clear correlation between molecular, ecophysiological, or geographical differences. However, salinity tolerance was associated with habitat type: intertidal strains grew best at high salinities; open-water strains grew best at low salinities. These data indicate the need to examine many strains of a species in both phylogenetic and ecological studies, especially where key-species are used to model ecological processes. [source] European Mathematical Genetics Meeting, Heidelberg, Germany, 12th,13th April 2007ANNALS OF HUMAN GENETICS, Issue 4 2007Article first published online: 28 MAY 200 Saurabh Ghosh 11 Indian Statistical Institute, Kolkata, India High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both. In this study, we develop statistical methods to extract the contribution of a common QTL to the total correlation between the components of a bivariate phenotype. Using data on bivariate phenotypes and marker genotypes for sib-pairs, we propose a test for linkage between a common QTL and a marker locus based on the conditional cross-sib trait correlations (trait 1 of sib 1 , trait 2 of sib 2 and conversely) given the identity-by-descent sharing at the marker locus. The null hypothesis cannot be rejected unless there exists a common QTL. We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from the Collaborative Study On The Genetics Of Alcoholism project. Rémi Kazma 1 , Catherine Bonaïti-Pellié 1 , Emmanuelle Génin 12 INSERM UMR-S535 and Université Paris Sud, Villejuif, 94817, France Keywords: Gene-environment interaction, sibling recurrence risk, exposure correlation Gene-environment interactions may play important roles in complex disease susceptibility but their detection is often difficult. Here we show how gene-environment interactions can be detected by investigating the degree of familial aggregation according to the exposure of the probands. In case of gene-environment interaction, the distribution of genotypes of affected individuals, and consequently the risk in relatives, depends on their exposure. We developed a test comparing the risks in sibs according to the proband exposure. To evaluate the properties of this new test, we derived the formulas for calculating the expected risks in sibs according to the exposure of probands for various values of exposure frequency, relative risk due to exposure alone, frequencies of latent susceptibility genotypes, genetic relative risks and interaction coefficients. We find that the ratio of risks when the proband is exposed and not exposed is a good indicator of the interaction effect. We evaluate the power of the test for various sample sizes of affected individuals. We conclude that this test is valuable for diseases with moderate familial aggregation, only when the role of the exposure has been clearly evidenced. Since a correlation for exposure among sibs might lead to a difference in risks among sibs in the different proband exposure strata, we also add an exposure correlation coefficient in the model. Interestingly, we find that when this correlation is correctly accounted for, the power of the test is not decreased and might even be significantly increased. Andrea Callegaro 1 , Hans J.C. Van Houwelingen 1 , Jeanine Houwing-Duistermaat 13 Dept. of Medical Statistics and Bioinformatics, Leiden University Medical Center, The Netherlands Keywords: Survival analysis, age at onset, score test, linkage analysis Non parametric linkage (NPL) analysis compares the identical by descent (IBD) sharing in sibling pairs to the expected IBD sharing under the hypothesis of no linkage. Often information is available on the marginal cumulative hazards (for example breast cancer incidence curves). Our aim is to extend the NPL methods by taking into account the age at onset of selected sibling pairs using these known marginal hazards. Li and Zhong (2002) proposed a (retrospective) likelihood ratio test based on an additive frailty model for genetic linkage analysis. From their model we derive a score statistic for selected samples which turns out to be a weighed NPL method. The weights depend on the marginal cumulative hazards and on the frailty parameter. A second approach is based on a simple gamma shared frailty model. Here, we simply test whether the score function of the frailty parameter depends on the excess IBD. We compare the performance of these methods using simulated data. Céline Bellenguez 1 , Carole Ober 2 , Catherine Bourgain 14 INSERM U535 and University Paris Sud, Villejuif, France 5 Department of Human Genetics, The University of Chicago, USA Keywords: Linkage analysis, linkage disequilibrium, high density SNP data Compared with microsatellite markers, high density SNP maps should be more informative for linkage analyses. However, because they are much closer, SNPs present important linkage disequilibrium (LD), which biases classical nonparametric multipoint analyses. This problem is even stronger in population isolates where LD extends over larger regions with a more stochastic pattern. We investigate the issue of linkage analysis with a 500K SNP map in a large and inbred 1840-member Hutterite pedigree, phenotyped for asthma. Using an efficient pedigree breaking strategy, we first identified linked regions with a 5cM microsatellite map, on which we focused to evaluate the SNP map. The only method that models LD in the NPL analysis is limited in both the pedigree size and the number of markers (Abecasis and Wigginton, 2005) and therefore could not be used. Instead, we studied methods that identify sets of SNPs with maximum linkage information content in our pedigree and no LD-driven bias. Both algorithms that directly remove pairs of SNPs in high LD and clustering methods were evaluated. Null simulations were performed to control that Zlr calculated with the SNP sets were not falsely inflated. Preliminary results suggest that although LD is strong in such populations, linkage information content slightly better than that of microsatellite maps can be extracted from dense SNP maps, provided that a careful marker selection is conducted. In particular, we show that the specific LD pattern requires considering LD between a wide range of marker pairs rather than only in predefined blocks. Peter Van Loo 1,2,3 , Stein Aerts 1,2 , Diether Lambrechts 4,5 , Bernard Thienpont 2 , Sunit Maity 4,5 , Bert Coessens 3 , Frederik De Smet 4,5 , Leon-Charles Tranchevent 3 , Bart De Moor 2 , Koen Devriendt 3 , Peter Marynen 1,2 , Bassem Hassan 1,2 , Peter Carmeliet 4,5 , Yves Moreau 36 Department of Molecular and Developmental Genetics, VIB, Belgium 7 Department of Human Genetics, University of Leuven, Belgium 8 Bioinformatics group, Department of Electrical Engineering, University of Leuven, Belgium 9 Department of Transgene Technology and Gene Therapy, VIB, Belgium 10 Center for Transgene Technology and Gene Therapy, University of Leuven, Belgium Keywords: Bioinformatics, gene prioritization, data fusion The identification of genes involved in health and disease remains a formidable challenge. Here, we describe a novel bioinformatics method to prioritize candidate genes underlying pathways or diseases, based on their similarity to genes known to be involved in these processes. It is freely accessible as an interactive software tool, ENDEAVOUR, at http://www.esat.kuleuven.be/endeavour. Unlike previous methods, ENDEAVOUR generates distinct prioritizations from multiple heterogeneous data sources, which are then integrated, or fused, into one global ranking using order statistics. ENDEAVOUR prioritizes candidate genes in a three-step process. First, information about a disease or pathway is gathered from a set of known "training" genes by consulting multiple data sources. Next, the candidate genes are ranked based on similarity with the training properties obtained in the first step, resulting in one prioritized list for each data source. Finally, ENDEAVOUR fuses each of these rankings into a single global ranking, providing an overall prioritization of the candidate genes. Validation of ENDEAVOUR revealed it was able to efficiently prioritize 627 genes in disease data sets and 76 genes in biological pathway sets, identify candidates of 16 mono- or polygenic diseases, and discover regulatory genes of myeloid differentiation. Furthermore, the approach identified YPEL1 as a novel gene involved in craniofacial development from a 2-Mb chromosomal region, deleted in some patients with DiGeorge-like birth defects. Finally, we are currently evaluating a pipeline combining array-CGH, ENDEAVOUR and in vivo validation in zebrafish to identify novel genes involved in congenital heart defects. Mark Broom 1 , Graeme Ruxton 2 , Rebecca Kilner 311 Mathematics Dept., University of Sussex, UK 12 Division of Environmental and Evolutionary Biology, University of Glasgow, UK 13 Department of Zoology, University of Cambridge, UK Keywords: Evolutionarily stable strategy, parasitism, asymmetric game Brood parasites chicks vary in the harm that they do to their companions in the nest. In this presentation we use game-theoretic methods to model this variation. Our model considers hosts which potentially abandon single nestlings and instead choose to re-allocate their reproductive effort to future breeding, irrespective of whether the abandoned chick is the host's young or a brood parasite's. The parasite chick must decide whether or not to kill host young by balancing the benefits from reduced competition in the nest against the risk of desertion by host parents. The model predicts that three different types of evolutionarily stable strategies can exist. (1) Hosts routinely rear depleted broods, the brood parasite always kills host young and the host never then abandons the nest. (2) When adult survival after deserting single offspring is very high, hosts always abandon broods of a single nestling and the parasite never kills host offspring, effectively holding them as hostages to prevent nest desertion. (3) Intermediate strategies, in which parasites sometimes kill their nest-mates and host parents sometimes desert nests that contain only a single chick, can also be evolutionarily stable. We provide quantitative descriptions of how the values given to ecological and behavioral parameters of the host-parasite system influence the likelihood of each strategy and compare our results with real host-brood parasite associations in nature. Martin Harrison 114 Mathematics Dept, University of Sussex, UK Keywords: Brood parasitism, games, host, parasite The interaction between hosts and parasites in bird populations has been studied extensively. Game theoretical methods have been used to model this interaction previously, but this has not been studied extensively taking into account the sequential nature of this game. We consider a model allowing the host and parasite to make a number of decisions, which depend on a number of natural factors. The host lays an egg, a parasite bird will arrive at the nest with a certain probability and then chooses to destroy a number of the host eggs and lay one of it's own. With some destruction occurring, either natural or through the actions of the parasite, the host chooses to continue, eject an egg (hoping to eject the parasite) or abandon the nest. Once the eggs have hatched the game then falls to the parasite chick versus the host. The chick chooses to destroy or eject a number of eggs. The final decision is made by the host, choosing whether to raise or abandon the chicks that are in the nest. We consider various natural parameters and probabilities which influence these decisions. We then use this model to look at real-world situations of the interactions of the Reed Warbler and two different parasites, the Common Cuckoo and the Brown-Headed Cowbird. These two parasites have different methods in the way that they parasitize the nests of their hosts. The hosts in turn have a different reaction to these parasites. Arne Jochens 1 , Amke Caliebe 2 , Uwe Roesler 1 , Michael Krawczak 215 Mathematical Seminar, University of Kiel, Germany 16 Institute of Medical Informatics and Statistics, University of Kiel, Germany Keywords: Stepwise mutation model, microsatellite, recursion equation, temporal behaviour We consider the stepwise mutation model which occurs, e.g., in microsatellite loci. Let X(t,i) denote the allelic state of individual i at time t. We compute expectation, variance and covariance of X(t,i), i=1,,,N, and provide a recursion equation for P(X(t,i)=z). Because the variance of X(t,i) goes to infinity as t grows, for the description of the temporal behaviour, we regard the scaled process X(t,i)-X(t,1). The results furnish a better understanding of the behaviour of the stepwise mutation model and may in future be used to derive tests for neutrality under this model. Paul O'Reilly 1 , Ewan Birney 2 , David Balding 117 Statistical Genetics, Department of Epidemiology and Public Health, Imperial, College London, UK 18 European Bioinformatics Institute, EMBL, Cambridge, UK Keywords: Positive selection, Recombination rate, LD, Genome-wide, Natural Selection In recent years efforts to develop population genetics methods that estimate rates of recombination and levels of natural selection in the human genome have intensified. However, since the two processes have an intimately related impact on genetic variation their inference is vulnerable to confounding. Genomic regions subject to recent selection are likely to have a relatively recent common ancestor and consequently less opportunity for historical recombinations that are detectable in contemporary populations. Here we show that selection can reduce the population-based recombination rate estimate substantially. In genome-wide studies for detecting selection we observe a tendency to highlight loci that are subject to low levels of recombination. We find that the outlier approach commonly adopted in such studies may have low power unless variable recombination is accounted for. We introduce a new genome-wide method for detecting selection that exploits the sensitivity to recent selection of methods for estimating recombination rates, while accounting for variable recombination using pedigree data. Through simulations we demonstrate the high power of the Ped/Pop approach to discriminate between neutral and adaptive evolution, particularly in the context of choosing outliers from a genome-wide distribution. Although methods have been developed showing good power to detect selection ,in action', the corresponding window of opportunity is small. In contrast, the power of the Ped/Pop method is maintained for many generations after the fixation of an advantageous variant Sarah Griffiths 1 , Frank Dudbridge 120 MRC Biostatistics Unit, Cambridge, UK Keywords: Genetic association, multimarker tag, haplotype, likelihood analysis In association studies it is generally too expensive to genotype all variants in all subjects. We can exploit linkage disequilibrium between SNPs to select a subset that captures the variation in a training data set obtained either through direct resequencing or a public resource such as the HapMap. These ,tag SNPs' are then genotyped in the whole sample. Multimarker tagging is a more aggressive adaptation of pairwise tagging that allows for combinations of two or more tag SNPs to predict an untyped SNP. Here we describe a new method for directly testing the association of an untyped SNP using a multimarker tag. Previously, other investigators have suggested testing a specific tag haplotype, or performing a weighted analysis using weights derived from the training data. However these approaches do not properly account for the imperfect correlation between the tag haplotype and the untyped SNP. Here we describe a straightforward approach to testing untyped SNPs using a missing-data likelihood analysis, including the tag markers as nuisance parameters. The training data is stacked on top of the main body of genotype data so there is information on how the tag markers predict the genotype of the untyped SNP. The uncertainty in this prediction is automatically taken into account in the likelihood analysis. This approach yields more power and also a more accurate prediction of the odds ratio of the untyped SNP. Anke Schulz 1 , Christine Fischer 2 , Jenny Chang-Claude 1 , Lars Beckmann 121 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany 22 Institute of Human Genetics, University of Heidelberg, Germany Keywords: Haplotype, haplotype sharing, entropy, Mantel statistics, marker selection We previously introduced a new method to map genes involved in complex diseases, using haplotype sharing-based Mantel statistics to correlate genetic and phenotypic similarity. Although the Mantel statistic is powerful in narrowing down candidate regions, the precise localization of a gene is hampered in genomic regions where linkage disequilibrium is so high that neighboring markers are found to be significant at similar magnitude and we are not able to discriminate between them. Here, we present a new approach to localize susceptibility genes by combining haplotype sharing-based Mantel statistics with an iterative entropy-based marker selection algorithm. For each marker at which the Mantel statistic is evaluated, the algorithm selects a subset of surrounding markers. The subset is chosen to maximize multilocus linkage disequilibrium, which is measured by the normalized entropy difference introduced by Nothnagel et al. (2002). We evaluated the algorithm with respect to type I error and power. Its ability to localize the disease variant was compared to the localization (i) without marker selection and (ii) considering haplotype block structure. Case-control samples were simulated from a set of 18 haplotypes, consisting of 15 SNPs in two haplotype blocks. The new algorithm gave correct type I error and yielded similar power to detect the disease locus compared to the alternative approaches. The neighboring markers were clearly less often significant than the causal locus, and also less often significant compared to the alternative approaches. Thus the new algorithm improved the precision of the localization of susceptibility genes. Mark M. Iles 123 Section of Epidemiology and Biostatistics, LIMM, University of Leeds, UK Keywords: tSNP, tagging, association, HapMap Tagging SNPs (tSNPs) are commonly used to capture genetic diversity cost-effectively. However, it is important that the efficacy of tSNPs is correctly estimated, otherwise coverage may be insufficient. If the pilot sample from which tSNPs are chosen is too small or the initial marker map too sparse, tSNP efficacy may be overestimated. An existing estimation method based on bootstrapping goes some way to correct for insufficient sample size and overfitting, but does not completely solve the problem. We describe a novel method, based on exclusion of haplotypes, that improves on the bootstrap approach. Using simulated data, the extent of the sample size problem is investigated and the performance of the bootstrap and the novel method are compared. We incorporate an existing method adjusting for marker density by ,SNP-dropping'. We find that insufficient sample size can cause large overestimates in tSNP efficacy, even with as many as 100 individuals, and the problem worsens as the region studied increases in size. Both the bootstrap and novel method correct much of this overestimate, with our novel method consistently outperforming the bootstrap method. We conclude that a combination of insufficient sample size and overfitting may lead to overestimation of tSNP efficacy and underpowering of studies based on tSNPs. Our novel approach corrects for much of this bias and is superior to the previous method. Sample sizes larger than previously suggested may still be required for accurate estimation of tSNP efficacy. This has obvious ramifications for the selection of tSNPs from HapMap data. Claudio Verzilli 1 , Juliet Chapman 1 , Aroon Hingorani 2 , Juan Pablo-Casas 1 , Tina Shah 2 , Liam Smeeth 1 , John Whittaker 124 Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, UK 25 Division of Medicine, University College London, UK Keywords: Meta-analysis, Genetic association studies We present a Bayesian hierarchical model for the meta-analysis of candidate gene studies with a continuous outcome. Such studies often report results from association tests for different, possibly study-specific and non-overlapping markers (typically SNPs) in the same genetic region. Meta analyses of the results at each marker in isolation are seldom appropriate as they ignore the correlation that may exist between markers due to linkage disequlibrium (LD) and cannot assess the relative importance of variants at each marker. Also such marker-wise meta analyses are restricted to only those studies that have typed the marker in question, with a potential loss of power. A better strategy is one which incorporates information about the LD between markers so that any combined estimate of the effect of each variant is corrected for the effect of other variants, as in multiple regression. Here we develop a Bayesian hierarchical linear regression that models the observed genotype group means and uses pairwise LD measurements between markers as prior information to make posterior inference on adjusted effects. The approach is applied to the meta analysis of 24 studies assessing the effect of 7 variants in the C-reactive protein (CRP) gene region on plasma CRP levels, an inflammatory biomarker shown in observational studies to be positively associated with cardiovascular disease. Cathryn M. Lewis 1 , Christopher G. Mathew 1 , Theresa M. Marteau 226 Dept. of Medical and Molecular Genetics, King's College London, UK 27 Department of Psychology, King's College London, UK Keywords: Risk, genetics, CARD15, smoking, model Recently progress has been made in identifying mutations that confer susceptibility to complex diseases, with the potential to use these mutations in determining disease risk. We developed methods to estimate disease risk based on genotype relative risks (for a gene G), exposure to an environmental factor (E), and family history (with recurrence risk ,R for a relative of type R). ,R must be partitioned into the risk due to G (which is modelled independently) and the residual risk. The risk model was then applied to Crohn's disease (CD), a severe gastrointestinal disease for which smoking increases disease risk approximately 2-fold, and mutations in CARD15 confer increased risks of 2.25 (for carriers of a single mutation) and 9.3 (for carriers of two mutations). CARD15 accounts for only a small proportion of the genetic component of CD, with a gene-specific ,S, CARD15 of 1.16, from a total sibling relative risk of ,S= 27. CD risks were estimated for high-risk individuals who are siblings of a CD case, and who also smoke. The CD risk to such individuals who carry two CARD15 mutations is approximately 0.34, and for those carrying a single CARD15 mutation the risk is 0.08, compared to a population prevalence of approximately 0.001. These results imply that complex disease genes may be valuable in estimating with greater precision than has hitherto been possible disease risks in specific, easily identified subgroups of the population with a view to prevention. Yurii Aulchenko 128 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Compression, information, bzip2, genome-wide SNP data, statistical genetics With advances in molecular technology, studies accessing millions of genetic polymorphisms in thousands of study subjects will soon become common. Such studies generate large amounts of data, whose effective storage and management is a challenge to the modern statistical genetics. Standard file compression utilities, such as Zip, Gzip and Bzip2, may be helpful to minimise the storage requirements. Less obvious is the fact that the data compression techniques may be also used in the analysis of genetic data. It is known that the efficiency of a particular compression algorithm depends on the probability structure of the data. In this work, we compared different standard and customised tools using the data from human HapMap project. Secondly, we investigate the potential uses of data compression techniques for the analysis of linkage, association and linkage disequilibrium Suzanne Leal 1 , Bingshan Li 129 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, USA Keywords: Consanguineous pedigrees, missing genotype data Missing genotype data can increase false-positive evidence for linkage when either parametric or nonparametric analysis is carried out ignoring intermarker linkage disequilibrium (LD). Previously it was demonstrated by Huang et al (2005) that no bias occurs in this situation for affected sib-pairs with unrelated parents when either both parents are genotyped or genotype data is available for two additional unaffected siblings when parental genotypes are missing. However, this is not the case for consanguineous pedigrees, where missing genotype data for any pedigree member within a consanguinity loop can increase false-positive evidence of linkage. The false-positive evidence for linkage is further increased when cryptic consanguinity is present. The amount of false-positive evidence for linkage is highly dependent on which family members are genotyped. When parental genotype data is available, the false-positive evidence for linkage is usually not as strong as when parental genotype data is unavailable. Which family members will aid in the reduction of false-positive evidence of linkage is highly dependent on which other family members are genotyped. For a pedigree with an affected proband whose first-cousin parents have been genotyped, further reduction in the false-positive evidence of linkage can be obtained by including genotype data from additional affected siblings of the proband or genotype data from the proband's sibling-grandparents. When parental genotypes are not available, false-positive evidence for linkage can be reduced by including in the analysis genotype data from either unaffected siblings of the proband or the proband's married-in-grandparents. Najaf Amin 1 , Yurii Aulchenko 130 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Genomic Control, pedigree structure, quantitative traits The Genomic Control (GC) method was originally developed to control for population stratification and cryptic relatedness in association studies. This method assumes that the effect of population substructure on the test statistics is essentially constant across the genome, and therefore unassociated markers can be used to estimate the effect of confounding onto the test statistic. The properties of GC method were extensively investigated for different stratification scenarios, and compared to alternative methods, such as the transmission-disequilibrium test. The potential of this method to correct not for occasional cryptic relations, but for regular pedigree structure, however, was not investigated before. In this work we investigate the potential of the GC method for pedigree-based association analysis of quantitative traits. The power and type one error of the method was compared to standard methods, such as the measured genotype (MG) approach and quantitative trait transmission-disequilibrium test. In human pedigrees, with trait heritability varying from 30 to 80%, the power of MG and GC approach was always higher than that of TDT. GC had correct type 1 error and its power was close to that of MG under moderate heritability (30%), but decreased with higher heritability. William Astle 1 , Chris Holmes 2 , David Balding 131 Department of Epidemiology and Public Health, Imperial College London, UK 32 Department of Statistics, University of Oxford, UK Keywords: Population structure, association studies, genetic epidemiology, statistical genetics In the analysis of population association studies, Genomic Control (Devlin & Roeder, 1999) (GC) adjusts the Armitage test statistic to correct the type I error for the effects of population substructure, but its power is often sub-optimal. Turbo Genomic Control (TGC) generalises GC to incorporate co-variation of relatedness and phenotype, retaining control over type I error while improving power. TGC is similar to the method of Yu et al. (2006), but we extend it to binary (case-control) in addition to quantitative phenotypes, we implement improved estimation of relatedness coefficients, and we derive an explicit statistic that generalizes the Armitage test statistic and is fast to compute. TGC also has similarities to EIGENSTRAT (Price et al., 2006) which is a new method based on principle components analysis. The problems of population structure(Clayton et al., 2005) and cryptic relatedness (Voight & Pritchard, 2005) are essentially the same: if patterns of shared ancestry differ between cases and controls, whether distant (coancestry) or recent (cryptic relatedness), false positives can arise and power can be diminished. With large numbers of widely-spaced genetic markers, coancestry can now be measured accurately for each pair of individuals via patterns of allele-sharing. Instead of modelling subpopulations, we work instead with a coancestry coefficient for each pair of individuals in the study. We explain the relationships between TGC, GC and EIGENSTRAT. We present simulation studies and real data analyses to illustrate the power advantage of TGC in a range of scenarios incorporating both substructure and cryptic relatedness. References Clayton, D. G.et al. (2005) Population structure, differential bias and genomic control in a large-scale case-control association study. Nature Genetics37(11) November 2005. Devlin, B. & Roeder, K. (1999) Genomic control for association studies. Biometics55(4) December 1999. Price, A. L.et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics38(8) (August 2006). Voight, B. J. & Pritchard, J. K. (2005) Confounding from cryptic relatedness in case-control association studies. Public Library of Science Genetics1(3) September 2005. Yu, J.et al. (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics38(2) February 2006. Hervé Perdry 1 , Marie-Claude Babron 1 , Françoise Clerget-Darpoux 133 INSERM U535 and Univ. Paris Sud, UMR-S 535, Villejuif, France Keywords: Modifier genes, case-parents trios, ordered transmission disequilibrium test A modifying locus is a polymorphic locus, distinct from the disease locus, which leads to differences in the disease phenotype, either by modifying the penetrance of the disease allele, or by modifying the expression of the disease. The effect of such a locus is a clinical heterogeneity that can be reflected by the values of an appropriate covariate, such as the age of onset, or the severity of the disease. We designed the Ordered Transmission Disequilibrium Test (OTDT) to test for a relation between the clinical heterogeneity, expressed by the covariate, and marker genotypes of a candidate gene. The method applies to trio families with one affected child and his parents. Each family member is genotyped at a bi-allelic marker M of a candidate gene. To each of the families is associated a covariate value; the families are ordered on the values of this covariate. As the TDT (Spielman et al. 1993), the OTDT is based on the observation of the transmission rate T of a given allele at M. The OTDT aims to find a critical value of the covariate which separates the sample of families in two subsamples in which the transmission rates are significantly different. We investigate the power of the method by simulations under various genetic models and covariate distributions. Acknowledgments H Perdry is funded by ARSEP. Pascal Croiseau 1 , Heather Cordell 2 , Emmanuelle Génin 134 INSERM U535 and University Paris Sud, UMR-S535, Villejuif, France 35 Institute of Human Genetics, Newcastle University, UK Keywords: Association, missing data, conditionnal logistic regression Missing data is an important problem in association studies. Several methods used to test for association need that individuals be genotyped at the full set of markers. Individuals with missing data need to be excluded from the analysis. This could involve an important decrease in sample size and a loss of information. If the disease susceptibility locus (DSL) is poorly typed, it is also possible that a marker in linkage disequilibrium gives a stronger association signal than the DSL. One may then falsely conclude that the marker is more likely to be the DSL. We recently developed a Multiple Imputation method to infer missing data on case-parent trios Starting from the observed data, a few number of complete data sets are generated by Markov-Chain Monte Carlo approach. These complete datasets are analysed using standard statistical package and the results are combined as described in Little & Rubin (2002). Here we report the results of simulations performed to examine, for different patterns of missing data, how often the true DSL gives the highest association score among different loci in LD. We found that multiple imputation usually correctly detect the DSL site even if the percentage of missing data is high. This is not the case for the naïve approach that consists in discarding trios with missing data. In conclusion, Multiple imputation presents the advantage of being easy to use and flexible and is therefore a promising tool in the search for DSL involved in complex diseases. Salma Kotti 1 , Heike Bickeböller 2 , Françoise Clerget-Darpoux 136 University Paris Sud, UMR-S535, Villejuif, France 37 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany Keywords: Genotype relative risk, internal controls, Family based analyses Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRRs. We will analytically derive the GRR estimators for the 1:1 and 1:3 matching and will present the results at the meeting. Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRR. We will analytically derive the GRR estimator for the 1:1 and 1:3 matching and will present the results at the meeting. Luigi Palla 1 , David Siegmund 239 Department of Mathematics,Free University Amsterdam, The Netherlands 40 Department of Statistics, Stanford University, California, USA Keywords: TDT, assortative mating, inbreeding, statistical power A substantial amount of Assortative Mating (AM) is often recorded on physical and psychological, dichotomous as well as quantitative traits that are supposed to have a multifactorial genetic component. In particular AM has the effect of increasing the genetic variance, even more than inbreeding because it acts across loci beside within loci, when the trait has a multifactorial origin. Under the assumption of a polygenic model for AM dating back to Wright (1921) and refined by Crow and Felsenstein (1968,1982), the effect of assortative mating on the power to detect genetic association in the Transmission Disequilibrium Test (TDT) is explored as parameters, such as the effective number of genes and the allelic frequency vary. The power is reflected by the non centrality parameter of the TDT and is expressed as a function of the number of trios, the relative risk of the heterozygous genotype and the allele frequency (Siegmund and Yakir, 2007). The noncentrality parameter of the relevant score statistic is updated considering the effect of AM which is expressed in terms of an ,effective' inbreeding coefficient. In particular, for dichotomous traits it is apparent that the higher the number of genes involved in the trait, the lower the loss in power due to AM. Finally an attempt is made to extend this relation to the Q-TDT (Rabinowitz, 1997), which involves considering the effect of AM also on the phenotypic variance of the trait of interest, under the assumption that AM affects only its additive genetic component. References Crow, & Felsenstein, (1968). The effect of assortative mating on the genetic composition of a population. Eugen.Quart.15, 87,97. Rabinowitz,, 1997. A Transmission Disequilibrium Test for Quantitative Trait Loci. Human Heredity47, 342,350. Siegmund, & Yakir, (2007) Statistics of gene mapping, Springer. Wright, (1921). System of mating.III. Assortative mating based on somatic resemblance. Genetics6, 144,161. Jérémie Nsengimana 1 , Ben D Brown 2 , Alistair S Hall 2 , Jenny H Barrett 141 Leeds Institute of Molecular Medicine, University of Leeds, UK 42 Leeds Institute for Genetics, Health and Therapeutics, University of Leeds, UK Keywords: Inflammatory genes, haplotype, coronary artery disease Genetic Risk of Acute Coronary Events (GRACE) is an initiative to collect cases of coronary artery disease (CAD) and their unaffected siblings in the UK and to use them to map genetic variants increasing disease risk. The aim of the present study was to test the association between CAD and 51 single nucleotide polymorphisms (SNPs) and their haplotypes from 35 inflammatory genes. Genotype data were available for 1154 persons affected before age 66 (including 48% before age 50) and their 1545 unaffected siblings (891 discordant families). Each SNP was tested for association to CAD, and haplotypes within genes or gene clusters were tested using FBAT (Rabinowitz & Laird, 2000). For the most significant results, genetic effect size was estimated using conditional logistic regression (CLR) within STATA adjusting for other risk factors. Haplotypes were assigned using HAPLORE (Zhang et al., 2005), which considers all parental mating types consistent with offspring genotypes and assigns them a probability of occurence. This probability was used in CLR to weight the haplotypes. In the single SNP analysis, several SNPs showed some evidence for association, including one SNP in the interleukin-1A gene. Analysing haplotypes in the interleukin-1 gene cluster, a common 3-SNP haplotype was found to increase the risk of CAD (P = 0.009). In an additive genetic model adjusting for covariates the odds ratio (OR) for this haplotype is 1.56 (95% CI: 1.16-2.10, p = 0.004) for early-onset CAD (before age 50). This study illustrates the utility of haplotype analysis in family-based association studies to investigate candidate genes. References Rabinowitz, D. & Laird, N. M. (2000) Hum Hered50, 211,223. Zhang, K., Sun, F. & Zhao, H. (2005) Bioinformatics21, 90,103. Andrea Foulkes 1 , Recai Yucel 1 , Xiaohong Li 143 Division of Biostatistics, University of Massachusetts, USA Keywords: Haploytpe, high-dimensional, mixed modeling The explosion of molecular level information coupled with large epidemiological studies presents an exciting opportunity to uncover the genetic underpinnings of complex diseases; however, several analytical challenges remain to be addressed. Characterizing the components to complex diseases inevitably requires consideration of synergies across multiple genetic loci and environmental and demographic factors. In addition, it is critical to capture information on allelic phase, that is whether alleles within a gene are in cis (on the same chromosome) or in trans (on different chromosomes.) In associations studies of unrelated individuals, this alignment of alleles within a chromosomal copy is generally not observed. We address the potential ambiguity in allelic phase in this high dimensional data setting using mixed effects models. Both a semi-parametric and fully likelihood-based approach to estimation are considered to account for missingness in cluster identifiers. In the first case, we apply a multiple imputation procedure coupled with a first stage expectation maximization algorithm for parameter estimation. A bootstrap approach is employed to assess sensitivity to variability induced by parameter estimation. Secondly, a fully likelihood-based approach using an expectation conditional maximization algorithm is described. Notably, these models allow for characterizing high-order gene-gene interactions while providing a flexible statistical framework to account for the confounding or mediating role of person specific covariates. The proposed method is applied to data arising from a cohort of human immunodeficiency virus type-1 (HIV-1) infected individuals at risk for therapy associated dyslipidemia. Simulation studies demonstrate reasonable power and control of family-wise type 1 error rates. Vivien Marquard 1 , Lars Beckmann 1 , Jenny Chang-Claude 144 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Genotyping errors, type I error, haplotype-based association methods It has been shown in several simulation studies that genotyping errors may have a great impact on the type I error of statistical methods used in genetic association analysis of complex diseases. Our aim was to investigate type I error rates in a case-control study, when differential and non-differential genotyping errors were introduced in realistic scenarios. We simulated case-control data sets, where individual genotypes were drawn from a haplotype distribution of 18 haplotypes with 15 markers in the APM1 gene. Genotyping errors were introduced following the unrestricted and symmetric with 0 edges error models described by Heid et al. (2006). In six scenarios, errors resulted from changes of one allele to another with predefined probabilities of 1%, 2.5% or 10%, respectively. A multiple number of errors per haplotype was possible and could vary between 0 and 15, the number of markers investigated. We examined three association methods: Mantel statistics using haplotype-sharing; a haplotype-specific score test; and Armitage trend test for single markers. The type I error rates were not influenced for any of all the three methods for a genotyping error rate of less than 1%. For higher error rates and differential errors, the type I error of the Mantel statistic was only slightly and of the Armitage trend test moderately increased. The type I error rates of the score test were highly increased. The type I error rates were correct for all three methods for non-differential errors. Further investigations will be carried out with different frequencies of differential error rates and focus on power. Arne Neumann 1 , Dörthe Malzahn 1 , Martina Müller 2 , Heike Bickeböller 145 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany 46 GSF-National Research Center for Environment and Health, Neuherberg & IBE-Institute of Epidemiology, Ludwig-Maximilians University München, Germany Keywords: Interaction, longitudinal, nonparametric Longitudinal data show the time dependent course of phenotypic traits. In this contribution, we consider longitudinal cohort studies and investigate the association between two candidate genes and a dependent quantitative longitudinal phenotype. The set-up defines a factorial design which allows us to test simultaneously for the overall gene effect of the loci as well as for possible gene-gene and gene time interaction. The latter would induce genetically based time-profile differences in the longitudinal phenotype. We adopt a non-parametric statistical test to genetic epidemiological cohort studies and investigate its performance by simulation studies. The statistical test was originally developed for longitudinal clinical studies (Brunner, Munzel, Puri, 1999 J Multivariate Anal 70:286-317). It is non-parametric in the sense that no assumptions are made about the underlying distribution of the quantitative phenotype. Longitudinal observations belonging to the same individual can be arbitrarily dependent on one another for the different time points whereas trait observations of different individuals are independent. The two loci are assumed to be statistically independent. Our simulations show that the nonparametric test is comparable with ANOVA in terms of power of detecting gene-gene and gene-time interaction in an ANOVA favourable setting. Rebecca Hein 1 , Lars Beckmann 1 , Jenny Chang-Claude 147 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Indirect association studies, interaction effects, linkage disequilibrium, marker allele frequency Association studies accounting for gene-environment interactions (GxE) may be useful for detecting genetic effects and identifying important environmental effect modifiers. Current technology facilitates very dense marker spacing in genetic association studies; however, the true disease variant(s) may not be genotyped. In this situation, an association between a gene and a phenotype may still be detectable, using genetic markers associated with the true disease variant(s) (indirect association). Zondervan and Cardon [2004] showed that the odds ratios (OR) of markers which are associated with the disease variant depend highly on the linkage disequilibrium (LD) between the variant and the markers, and whether the allele frequencies match and thereby influence the sample size needed to detect genetic association. We examined the influence of LD and allele frequencies on the sample size needed to detect GxE in indirect association studies, and provide tables for sample size estimation. For discordant allele frequencies and incomplete LD, sample sizes can be unfeasibly large. The influence of both factors is stronger for disease loci with small rather than moderate to high disease allele frequencies. A decline in D' of e.g. 5% has less impact on sample size than increasing the difference in allele frequencies by the same percentage. Assuming 80% power, large interaction effects can be detected using smaller sample sizes than those needed for the detection of main effects. The detection of interaction effects involving rare alleles may not be possible. Focussing only on marker density can be a limited strategy in indirect association studies for GxE. Cyril Dalmasso 1 , Emmanuelle Génin 2 , Catherine Bourgain 2 , Philippe Broët 148 JE 2492 , Univ. Paris-Sud, France 49 INSERM UMR-S 535 and University Paris Sud, Villejuif, France Keywords: Linkage analysis, Multiple testing, False Discovery Rate, Mixture model In the context of genome-wide linkage analyses, where a large number of statistical tests are simultaneously performed, the False Discovery Rate (FDR) that is defined as the expected proportion of false discoveries among all discoveries is nowadays widely used for taking into account the multiple testing problem. Other related criteria have been considered such as the local False Discovery Rate (lFDR) that is a variant of the FDR giving to each test its own measure of significance. The lFDR is defined as the posterior probability that a null hypothesis is true. Most of the proposed methods for estimating the lFDR or the FDR rely on distributional assumption under the null hypothesis. However, in observational studies, the empirical null distribution may be very different from the theoretical one. In this work, we propose a mixture model based approach that provides estimates of the lFDR and the FDR in the context of large-scale variance component linkage analyses. In particular, this approach allows estimating the empirical null distribution, this latter being a key quantity for any simultaneous inference procedure. The proposed method is applied on a real dataset. Arief Gusnanto 1 , Frank Dudbridge 150 MRC Biostatistics Unit, Cambridge UK Keywords: Significance, genome-wide, association, permutation, multiplicity Genome-wide association scans have introduced statistical challenges, mainly in the multiplicity of thousands of tests. The question of what constitutes a significant finding remains somewhat unresolved. Permutation testing is very time-consuming, whereas Bayesian arguments struggle to distinguish direct from indirect association. It seems attractive to summarise the multiplicity in a simple form that allows users to avoid time-consuming permutations. A standard significance level would facilitate reporting of results and reduce the need for permutation tests. This is potentially important because current scans do not have full coverage of the whole genome, and yet, the implicit multiplicity is genome-wide. We discuss some proposed summaries, with reference to the empirical null distribution of the multiple tests, approximated through a large number of random permutations. Using genome-wide data from the Wellcome Trust Case-Control Consortium, we use a sub-sampling approach with increasing density to estimate the nominal p-value to obtain family-wise significance of 5%. The results indicate that the significance level is converging to about 1e-7 as the marker spacing becomes infinitely dense. We considered the concept of an effective number of independent tests, and showed that when used in a Bonferroni correction, the number varies with the overall significance level, but is roughly constant in the region of interest. We compared several estimators of the effective number of tests, and showed that in the region of significance of interest, Patterson's eigenvalue based estimator gives approximately the right family-wise error rate. Michael Nothnagel 1 , Amke Caliebe 1 , Michael Krawczak 151 Institute of Medical Informatics and Statistics, University Clinic Schleswig-Holstein, University of Kiel, Germany Keywords: Association scans, Bayesian framework, posterior odds, genetic risk, multiplicative model Whole-genome association scans have been suggested to be a cost-efficient way to survey genetic variation and to map genetic disease factors. We used a Bayesian framework to investigate the posterior odds of a genuine association under multiplicative disease models. We demonstrate that the p value alone is not a sufficient means to evaluate the findings in association studies. We suggest that likelihood ratios should accompany p values in association reports. We argue, that, given the reported results of whole-genome scans, more associations should have been successfully replicated if the consistently made assumptions about considerable genetic risks were correct. We conclude that it is very likely that the vast majority of relative genetic risks are only of the order of 1.2 or lower. Clive Hoggart 1 , Maria De Iorio 1 , John Whittakker 2 , David Balding 152 Department of Epidemiology and Public Health, Imperial College London, UK 53 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: Genome-wide association analyses, shrinkage priors, Lasso Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants of small effect, which is a plausible scenario for many complex diseases. Moreover, many simulation studies assume a single causal variant and so more complex realities are ignored. Analysing large numbers of variants simultaneously is now becoming feasible, thanks to developments in Bayesian stochastic search methods. We pose the problem of SNP selection as variable selection in a regression model. In contrast to single SNP tests this approach simultaneously models the effect of all SNPs. SNPs are selected by a Bayesian interpretation of the lasso (Tibshirani, 1996); the maximum a posterior (MAP) estimate of the regression coefficients, which have been given independent, double exponential prior distributions. The double exponential distribution is an example of a shrinkage prior, MAP estimates with shrinkage priors can be zero, thus all SNPs with non zero regression coefficients are selected. In addition to the commonly-used double exponential (Laplace) prior, we also implement the normal exponential gamma prior distribution. We show that use of the Laplace prior improves SNP selection in comparison with single -SNP tests, and that the normal exponential gamma prior leads to a further improvement. Our method is fast and can handle very large numbers of SNPs: we demonstrate its performance using both simulated and real genome-wide data sets with 500 K SNPs, which can be analysed in 2 hours on a desktop workstation. Mickael Guedj 1,2 , Jerome Wojcik 2 , Gregory Nuel 154 Laboratoire Statistique et Génome, Université d'Evry, Evry France 55 Serono Pharmaceutical Research Institute, Plan-les-Ouates, Switzerland Keywords: Local Replication, Local Score, Association In gene-mapping, replication of initial findings has been put forwards as the approach of choice for filtering false-positives from true signals for underlying loci. In practice, such replications are however too poorly observed. Besides the statistical and technical-related factors (lack of power, multiple-testing, stratification, quality control,) inconsistent conclusions obtained from independent populations might result from real biological differences. In particular, the high degree of variation in the strength of LD among populations of different origins is a major challenge to the discovery of genes. Seeking for Local Replications (defined as the presence of a signal of association in a same genomic region among populations) instead of strict replications (same locus, same risk allele) may lead to more reliable results. Recently, a multi-markers approach based on the Local Score statistic has been proposed as a simple and efficient way to select candidate genomic regions at the first stage of genome-wide association studies. Here we propose an extension of this approach adapted to replicated association studies. Based on simulations, this method appears promising. In particular it outperforms classical simple-marker strategies to detect modest-effect genes. Additionally it constitutes, to our knowledge, a first framework dedicated to the detection of such Local Replications. Juliet Chapman 1 , Claudio Verzilli 1 , John Whittaker 156 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: FDR, Association studies, Bayesian model selection As genomewide association studies become commonplace there is debate as to how such studies might be analysed and what we might hope to gain from the data. It is clear that standard single locus approaches are limited in that they do not adjust for the effects of other loci and problematic since it is not obvious how to adjust for multiple comparisons. False discovery rates have been suggested, but it is unclear how well these will cope with highly correlated genetic data. We consider the validity of standard false discovery rates in large scale association studies. We also show that a Bayesian procedure has advantages in detecting causal loci amongst a large number of dependant SNPs and investigate properties of a Bayesian FDR. Peter Kraft 157 Harvard School of Public Health, Boston USA Keywords: Gene-environment interaction, genome-wide association scans Appropriately analyzed two-stage designs,where a subset of available subjects are genotyped on a genome-wide panel of markers at the first stage and then a much smaller subset of the most promising markers are genotyped on the remaining subjects,can have nearly as much power as a single-stage study where all subjects are genotyped on the genome-wide panel yet can be much less expensive. Typically, the "most promising" markers are selected based on evidence for a marginal association between genotypes and disease. Subsequently, the few markers found to be associated with disease at the end of the second stage are interrogated for evidence of gene-environment interaction, mainly to understand their impact on disease etiology and public health impact. However, this approach may miss variants which have a sizeable effect restricted to one exposure stratum and therefore only a modest marginal effect. We have proposed to use information on the joint effects of genes and a discrete list of environmental exposures at the initial screening stage to select promising markers for the second stage [Kraft et al Hum Hered 2007]. This approach optimizes power to detect variants that have a sizeable marginal effect and variants that have a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. As an example, I discuss a proposed genome-wide association scan for Type II diabetes susceptibility variants based in several large nested case-control studies. Beate Glaser 1 , Peter Holmans 158 Biostatistics and Bioinformatics Unit, Cardiff University, School of Medicine, Heath Park, Cardiff, UK Keywords: Combined case-control and trios analysis, Power, False-positive rate, Simulation, Association studies The statistical power of genetic association studies can be enhanced by combining the analysis of case-control with parent-offspring trio samples. Various combined analysis techniques have been recently developed; as yet, there have been no comparisons of their power. This work was performed with the aim of identifying the most powerful method among available combined techniques including test statistics developed by Kazeem and Farrall (2005), Nagelkerke and colleagues (2004) and Dudbridge (2006), as well as a simple combination of ,2-statistics from single samples. Simulation studies were performed to investigate their power under different additive, multiplicative, dominant and recessive disease models. False-positive rates were determined by studying the type I error rates under null models including models with unequal allele frequencies between the single case-control and trios samples. We identified three techniques with equivalent power and false-positive rates, which included modifications of the three main approaches: 1) the unmodified combined Odds ratio estimate by Kazeem & Farrall (2005), 2) a modified approach of the combined risk ratio estimate by Nagelkerke & colleagues (2004) and 3) a modified technique for a combined risk ratio estimate by Dudbridge (2006). Our work highlights the importance of studies investigating test performance criteria of novel methods, as they will help users to select the optimal approach within a range of available analysis techniques. David Almorza 1 , M.V. Kandus 2 , Juan Carlos Salerno 2 , Rafael Boggio 359 Facultad de Ciencias del Trabajo, University of Cádiz, Spain 60 Instituto de Genética IGEAF, Buenos Aires, Argentina 61 Universidad Nacional de La Plata, Buenos Aires, Argentina Keywords: Principal component analysis, maize, ear weight, inbred lines The objective of this work was to evaluate the relationship among different traits of the ear of maize inbred lines and to group genotypes according to its performance. Ten inbred lines developed at IGEAF (INTA Castelar) and five public inbred lines as checks were used. A field trial was carried out in Castelar, Buenos Aires (34° 36' S , 58° 39' W) using a complete randomize design with three replications. At harvest, individual weight (P.E.), diameter (D.E.), row number (N.H.) and length (L.E.) of the ear were assessed. A principal component analysis, PCA, (Infostat 2005) was used, and the variability of the data was depicted with a biplot. Principal components 1 and 2 (CP1 and CP2) explained 90% of the data variability. CP1 was correlated with P.E., L.E. and D.E., meanwhile CP2 was correlated with N.H. We found that individual weight (P.E.) was more correlated with diameter of the ear (D.E.) than with length (L.E). Five groups of inbred lines were distinguished: with high P.E. and mean N.H. (04-70, 04-73, 04-101 and MO17), with high P.E. but less N.H. (04-61 and B14), with mean P.E. and N.H. (B73, 04-123 and 04-96), with high N.H. but less P.E. (LP109, 04-8, 04-91 and 04-76) and with low P.E. and low N.H. (LP521 and 04-104). The use of PCA showed which variables had more incidence in ear weight and how is the correlation among them. Moreover, the different groups found with this analysis allow the evaluation of inbred lines by several traits simultaneously. Sven Knüppel 1 , Anja Bauerfeind 1 , Klaus Rohde 162 Department of Bioinformatics, MDC Berlin, Germany Keywords: Haplotypes, association studies, case-control, nuclear families The area of gene chip technology provides a plethora of phase-unknown SNP genotypes in order to find significant association to some genetic trait. To circumvent possibly low information content of a single SNP one groups successive SNPs and estimates haplotypes. Haplotype estimation, however, may reveal ambiguous haplotype pairs and bias the application of statistical methods. Zaykin et al. (Hum Hered, 53:79-91, 2002) proposed the construction of a design matrix to take this ambiguity into account. Here we present a set of functions written for the Statistical package R, which carries out haplotype estimation on the basis of the EM-algorithm for individuals (case-control) or nuclear families. The construction of a design matrix on basis of estimated haplotypes or haplotype pairs allows application of standard methods for association studies (linear, logistic regression), as well as statistical methods as haplotype sharing statistics and TDT-Test. Applications of these methods to genome-wide association screens will be demonstrated. Manuela Zucknick 1 , Chris Holmes 2 , Sylvia Richardson 163 Department of Epidemiology and Public Health, Imperial College London, UK 64 Department of Statistics, Oxford Center for Gene Function, University of Oxford, UK Keywords: Bayesian, variable selection, MCMC, large p, small n, structured dependence In large-scale genomic applications vast numbers of markers or genes are scanned to find a few candidates which are linked to a particular phenotype. Statistically, this is a variable selection problem in the "large p, small n" situation where many more variables than samples are available. An additional feature is the complex dependence structure which is often observed among the markers/genes due to linkage disequilibrium or their joint involvement in biological processes. Bayesian variable selection methods using indicator variables are well suited to the problem. Binary phenotypes like disease status are common and both Bayesian probit and logistic regression can be applied in this context. We argue that logistic regression models are both easier to tune and to interpret than probit models and implement the approach by Holmes & Held (2006). Because the model space is vast, MCMC methods are used as stochastic search algorithms with the aim to quickly find regions of high posterior probability. In a trade-off between fast-updating but slow-moving single-gene Metropolis-Hastings samplers and computationally expensive full Gibbs sampling, we propose to employ the dependence structure among the genes/markers to help decide which variables to update together. Also, parallel tempering methods are used to aid bold moves and help avoid getting trapped in local optima. Mixing and convergence of the resulting Markov chains are evaluated and compared to standard samplers in both a simulation study and in an application to a gene expression data set. Reference Holmes, C. C. & Held, L. (2006) Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis1, 145,168. Dawn Teare 165 MMGE, University of Sheffield, UK Keywords: CNP, family-based analysis, MCMC Evidence is accumulating that segmental copy number polymorphisms (CNPs) may represent a significant portion of human genetic variation. These highly polymorphic systems require handling as phenotypes rather than co-dominant markers, placing new demands on family-based analyses. We present an integrated approach to meet these challenges in the form of a graphical model, where the underlying discrete CNP phenotype is inferred from the (single or replicate) quantitative measure within the analysis, whilst assuming an allele based system segregating through the pedigree. [source] | |||||||||||||