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Single Sample (single + sample)
Selected AbstractsMorphological properties of isolated galaxies vs. isolation criteriaASTRONOMISCHE NACHRICHTEN, Issue 9-10 2009I.B. Vavilova Abstract We studied the morphological properties of isolated galaxies samples in dependence on the isolation parameter and properties of primary catalogs. With this aim we identified the samples of single and isolated galaxies from SDSS DR5 (Single and QIsol) with the 3D Voronoi tessellation method (Elyiv et al. 2009). We found that in comparison with other samples of isolated galaxies, the QIsol sample contains an excess of late-type galaxies, especially with a low luminosity and BCG/Im/Irr morphology. We also showed that the fractions of early type galaxies in QIsol SDSS DR5 sample and samples 2MIG (Karachentseva et al. 2010) and CIG (Karachentseva et al. 1973; Hernandez-Toledo et al. 2008) are in a good agreement (16,19 %), but Allam's (Allam et al. 2005) and Prada's (Prada et al. 2003) SDSS DR1 samples show a higher excess of the early type galaxies that can be explained by the selection criteria and morphology definition method. We found a weak relation between isolation parameter and color index for the Single sample that may indicate that even in the low dense environment the morphology density relation is observed. We conclude that morphological properties of the resulting sample of isolated galaxies are highly dependent on the primary catalogue from which the galaxies were selected. Moreover, the selection criterion is also important but plays a secondary role in the resulting morphological content, color indices distribution and other parameters of the isolated galaxy samples. Only four galaxies are common in the 2MIG, QIsol, and CIG samples, namely UGC5184, UGC6121, UGC8495, and UGC9598, that allows to consider them as really most isolated galaxies (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Photonic dating of prehistoric irrigation canals at Phoenix, Arizona, U.S.A.,GEOARCHAEOLOGY: AN INTERNATIONAL JOURNAL, Issue 1 2004Glenn W. Berger A number of archeological features, including in-filled irrigation canals of uncertain prehistoric age, occur within the Holocene floodplain of the Salt River at Phoenix, Arizona. In the first attempt to date irrigation-canal sediments using luminescence methods, we obtained age estimates of 1640 ± 190 yr B.P. (1,) (multi-aliquot or MA) and 1621 ± 95 yr B.P. (post-IR single-aliquot-regenerative-dose or SAR) for a single sample from the base of the oldest canal-infilling deposits (all IR-PSL ages reported in this article are in calendar years before A.D. 2001). For the remaining canal samples, weighted mean luminescence ages of 819 ± 45 yr (MA) and 826 ± 32 yr (post-IR SAR) were obtained. Thus from photonic dating we can resolve the first and last phases of canal use at this Phoenix site: initiation at ca. 1600 years ago and final use at ca. 800 years ago. These results demonstrate the power of SAR luminescence sediment dating to enhance our understanding of prehistoric irrigation-canal development and usage here and elsewhere in the world. © 2004 Wiley Periodicals, Inc. [source] Eclogites from the Chinese continental scientific drilling borehole, their petrology and different P-T evolutionsISLAND ARC, Issue 4 2007Yong-Feng Zhu Abstract Four phengite-bearing eclogites, taken from different depths of the Chinese continental scientific drilling (CCSD) borehole in the Sulu ultrahigh pressure terrane, eastern China, were studied with the electron microprobe. The compositional zonations of garnet and omphacite are moderate, whereas phengite compositions generally vary significantly in a single sample from core to rim by decrease of the Si content. Various geothermobarometric methods were applied to constrain the P-T conditions of these eclogites on the basis of the compositional variability of the above minerals. The constrained P-T path for sample B218 is characterized by pressure decrease from ca 3.0 GPa (ca 600°C) to 1.3 GPa (ca 550°C). Eclogite B310 yielded P-T conditions of 3.0 GPa and 750°C. The path for eclogite B1008 starts at about 650°C and 3.6,3.9 GPa (stage I) followed by a pressure decrease to 2.8,3.0 GPa and a significant temperature rise (stages II and IIIa, 750,810°C). Afterwards, this rock cooled down to 620,660°C at still high pressures (2.5,2.7 GPa, stage IIIb). Retrograde conditions were about 670°C and 1.3 GPa (stage IV). Eclogite B1039 yielded a P-T path starting at ca 600°C and 3.3,3.9 GPa (stage I). A pressure decrease to about 3.0 GPa (stage II, 590,610°C) and then a moderate isobaric temperature increase to ca 630°C (stage III) followed. Stage IV is characterized by temperatures of 650°C at pressures close to 1.3 GPa. During and after this stage (hydrous) fluids partially rich in potassium penetrated the rocks causing minor changes. Relatively high oxygen fugacities led to andradite and magnetite among the newly formed minerals. We think that the above findings can be best explained by mass flow in a subduction channel. Thus, we conclude that the assembly of UHP rocks of the CCSD site, eclogites, quartzofeldspathic rocks, and peridotites, cannot represent a crustal section that was already coherent at UHP conditions as it is the common belief currently. The coherency was attained after significant exhumation of these UHP rocks. [source] Quantitative analysis of total mitochondrial DNA: Competitive polymerase chain reaction versus real-time polymerase chain reactionJOURNAL OF BIOCHEMICAL AND MOLECULAR TOXICOLOGY, Issue 4 2004Hari K. Bhat Abstract An efficient and effective method for quantification of small amounts of nucleic acids contained within a sample specimen would be an important diagnostic tool for determining the content of mitochondrial DNA (mtDNA) in situations where the depletion thereof may be a contributing factor to the exhibited pathology phenotype. This study compares two quantification assays for calculating the total mtDNA molecule number per nanogram of total genomic DNA isolated from human blood, through the amplification of a 613-bp region on the mtDNA molecule. In one case, the mtDNA copy number was calculated by standard competitive polymerase chain reaction (PCR) technique that involves co-amplification of target DNA with various dilutions of a nonhomologous internal competitor that has the same primer binding sites as the target sequence, and subsequent determination of an equivalence point of target and competitor concentrations. In the second method, the calculation of copy number involved extrapolation from the fluorescence versus copy number standard curve generated by real-time PCR using various dilutions of the target amplicon sequence. While the mtDNA copy number was comparable using the two methods (4.92 ± 1.01 × 104 molecules/ng total genomic DNA using competitive PCR vs 4.90 ± 0.84 × 104 molecules/ng total genomic DNA using real-time PCR), both inter- and intraexperimental variance were significantly lower using the real-time PCR analysis. On the basis of reproducibility, assay complexity, and overall efficiency, including the time requirement and number of PCR reactions necessary for the analysis of a single sample, we recommend the real-time PCR quantification method described here, as its versatility and effectiveness will undoubtedly be of great use in various kinds of research related to mitochondrial DNA damage- and depletion-associated disorders. © 2004 Wiley Periodicals, Inc. J Biochem Mol Toxicol 18:180,186, 2004 Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/jbt.20024 [source] Evaluation of stratus® CS Stat fluorimetric analyser for measurement of cardiac markers Troponin I (cTnI), creatine kinase MB (CK-MB), and myoglobinJOURNAL OF CLINICAL LABORATORY ANALYSIS, Issue 6 2001Bénédicte Bénéteau-Burnat Abstract Myoglobin, CK-MB, and Troponin I (cTnI) are cardiac muscle necrosis markers that are useful for detecting acute myocardial infarction (AMI). The Stratus® CS (Dade Behring, Inc.) is a discrete fluorimetric immunoassay analyser designed for the determination of the three cardiac markers from a single sample of whole blood or plasma. Overall analytical performances of the Stratus® CS provided by Dade Behring were evaluated according to the French Society of Clinical Biology guidelines. Within-run imprecision (n = 20) for the three parameters at three levels gave values under 5%, whereas CVs for between-run imprecision (n = 20) were under 6%. The sensitivities were 0.03 ,g/L for cTnI and 0.4 ,g/L for CK-MB. Linearities extended from 0,50 ,g/L for cTnI, 0,140 ,g/L for CK-MB, and 1,900 ,g/L for myoglobin. The results, particularly those obtained on whole-blood samples, correlated well with those obtained on Stratus® II. We did not find any interference with haemolysis, icterus, or lipemia. The system was very easy to use, and fulfills the requirements for the analysis of the three cardiac markers in patients with acute chest pain in emergency situations. J. Clin. Lab. Anal. 15:314,318, 2001. © 2001 Wiley-Liss, Inc. [source] Investigation into the protein composition of human tear fluid using centrifugal filters and drop coating deposition Raman spectroscopyJOURNAL OF RAMAN SPECTROSCOPY, Issue 2 2009Jacob Filik Abstract Drop coating deposition Raman spectroscopy (DCDRS) is a simple method of analysing weak protein solutions. This study is another step in evaluating the analysis of tear fluid by DCDRS as a future medical diagnostic technique. The main aims of this study are to determine whether the DCDR spectra from tear samples contain signals from more than one protein (so relative levels can be measured) and, if so, are the proteins homogeneously distributed in the dried ring of the deposited material. Tear samples were collected from four healthy volunteers and pooled prior to analysis. Proteins were separated by mass into three groups using centrifugal filters. These groups contained proteins with (1) masses greater than 100 kDa, (2) masses between 100 and 50 kDa and (3) masses between 50 and 3 kDa. DCDR spectra from each of these protein group solutions displayed significant differences, confirming that the mass separation had been successful. When used as basis vectors for least-squares fitting, these spectra (and that of urea) produced excellent fits to the normal tear spectra. Least-squares fitting of spectra from the same point on a single sample and from several drops of the same sample showed that the tear DCDR spectra were highly reproducible. Raman point mapping of the tear ring showed significant radial ring variation, especially towards the outer edge of the ring. The specific peak changes in the protein signal across the ring suggested that the difference in the outer edge was due to protein desiccation as opposed to inhomogeneous protein deposition. Copyright © 2008 John Wiley & Sons, Ltd. [source] CURRENT-STATUS SURVIVAL ANALYSIS METHODOLOGY APPLIED TO ESTIMATING SENSORY SHELF LIFE OF READY-TO-EAT LETTUCE (LACTUCA SATIVA)JOURNAL OF SENSORY STUDIES, Issue 2 2008MABEL ARANEDA ABSTRACT The objective of the present work was to develop a method for predicting sensory shelf life for situations in which each consumer evaluates only one sample corresponding to one storage time. This type of data is known as current-status data in survival analysis statistics. The methodology was applied to estimate the sensory shelf life of ready-to-eat lettuce (Lactuca sativa var. capitata cv."Alpha"). For each of six storage times, 50,52 consumers answered yes or no to whether they would normally consume the presented sample. The results were satisfactory, showing that the methodology can be applied when necessary. The Weibull model was found adequate to model the data. Estimated shelf lives ± 95% confidence intervals were 11.3 ± 1.2 days and 15.5 ± 0.9 days for a 25% and a 50% consumer rejection probability, respectively. PRACTICAL APPLICATIONS When considering shelf-life evaluations by consumers, the first idea is to have each consumer evaluate six or seven samples with different storage times in a single session. To do this, a reverse storage design is necessary, and in the case of a product such as lettuce, it would lead to different batches being confused with storage times. The methodology proposed in this article avoids this problem by having each consumer evaluate a single sample. Another issue with consumers tasting several samples in a single session is how representative this situation is of real consumption. The present methodology allows for a consumer to take home, e.g., a bottle of beer with an established storage time, and later collecting the information as to whether they found the beer acceptable or not. This is a situation much closer to real consumption. [source] Aflatoxin contamination of consumer milk caused by contaminated rice by-products in compound cattle feedJOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, Issue 2 2009Erik Nordkvist Abstract BACKGROUND: Elevated levels of aflatoxin M1 were observed in routine checks of consumer milk in southern Sweden in early 2006. A trace-back study revealed contaminated milk from several farms, and a total of 68 farms were banned from delivering milk to dairies for shorter or longer periods. The maximum level of aflatoxin M1 in a single sample from an individual farm was 257 ng kg,1 fresh milk. RESULTS: Aflatoxin analyses of commercial compound feed revealed that the contamination originated from the ingredient rice feed meal, a by-product from the preparation of Basmati rice for human consumption. Up to 56 µg kg,1 of aflatoxin B1 was found in rice feed meal at one feed mill. CONCLUSION: The present example shows that an aflatoxin-contaminated minor feed ingredient included at less than 10% (w/w) of compound cattle feed can significantly contaminate the milk produced. This emphasises the need for effective monitoring of the feed chain of food-producing animals in order to prevent food contamination. Copyright © 2008 Society of Chemical Industry [source] A FIELD-BASED METHOD FOR ESTIMATING AGE IN FREE-RANGING STELLER SEA LIONS (EUMETOPIAS JUBATUS) LESS THAN TWENTY-FOUR MONTHS OF AGEMARINE MAMMAL SCIENCE, Issue 2 2007James C. King Abstract Studies of health, survival, and development of juvenile Alaskan Steller sea lions (Eumetopias jubatus, SSL) require accurate estimates of age for wild-captured animals. However, the value and accuracy of several potential predictors of age have not been assessed with data from known-age free-ranging animals. During 2001,2005, forty-six individual SSL originally branded or tagged at ,6 mo of age were recaptured by the Alaska Department of Fish and Game (ADF&G). Using a series of general linear models, we evaluated the ability of morphometrics measurements: permanent canine tooth length (CTL), diastema (DIAS), whisker length (WHIS), and dorsal standard length (DSL) to predict the age of forty-six known-age juveniles (n= 46 ,23 mo of age). Permanent CTL was the strongest individual predictor (r2= 0.80); followed by DSL, DIAS, and WHIS (r2= 0.70, 0.56, and 0.45, respectively). The inclusion of a single sample from a 44-mo-old sea lion suggested quadratic relationships between age and all predictors for older animals. Only models including CTL predicted age to within 6 mo of known age. The equation Age = (,3.0112 +[0.6726 * CTL]+[0.4965 * DIAS]) allows for accurate age estimates of SSL ,23 mo for both sexes. [source] An introduction to medical statistics for health care professionals: Hypothesis tests and estimationMUSCULOSKELETAL CARE, Issue 2 2005Elaine Thomas PhD MSc BSc Lecturer in Biostatistics Abstract This article is the second in a series of three that will give health care professionals (HCPs) a sound introduction to medical statistics (Thomas, 2004). The objective of research is to find out about the population at large. However, it is generally not possible to study the whole of the population and research questions are addressed in an appropriate study sample. The next crucial step is then to use the information from the sample of individuals to make statements about the wider population of like individuals. This procedure of drawing conclusions about the population, based on study data, is known as inferential statistics. The findings from the study give us the best estimate of what is true for the relevant population, given the sample is representative of the population. It is important to consider how accurate this best estimate is, based on a single sample, when compared to the unknown population figure. Any difference between the observed sample result and the population characteristic is termed the sampling error. This article will cover the two main forms of statistical inference (hypothesis tests and estimation) along with issues that need to be addressed when considering the implications of the study results. Copyright © 2005 Whurr Publishers Ltd. [source] Detection of four oxidation sites in viral prolyl-4-hydroxylase by top-down mass spectrometryPROTEIN SCIENCE, Issue 10 2003Ying Ge Abstract Oxidative inactivation is a common problem for enzymatic reactions that proceed via iron oxo intermediates. In an investigation of the inactivation of a viral prolyl-4-hydroxylase (26 kD), electrospray mass spectrometry (MS) directly shows the degree of oxidation under varying experimental conditions, but indicates the addition at most of three oxygen atoms per molecule. Thus, molecular ion masses (M + nO) of one sample indicate the oxygen atom adducts n = 0, 1, 2, 3, and 4 of 35, 41, 19, 5 ± 3, and <2%, respectively; "top-down" MS/MS of these ions show oxidation at the sites R28,V31, E95,F107, and K216 of 22%, 28%, and 34%, respectively, but with a possible (,4%) fourth site at V125,D150. However, for the doubly oxidized molecular ions (increasing the precursor oxygen content from 0.94 to 2), MS/MS showed an easily observable ,13% oxygen at the V125,D150 site. For the "bottom-up" approach, detection of the ,4% oxidation at the V125,D150 site by MS analysis of a proteolysis mixture would have been very difficult. The unmodified peptide containing this site would represent a few percent of the proteolysis mixture; the oxidized peptide not only would be just ,4% of this, but the uniqueness of its mass value (,1,2 kD) would be far less than the 11,933 Dalton value used here. Using different molecular ion precursors for top-down MS/MS also provides kinetic data from a single sample, that is, from molecular ions with 0.94 and 2 oxygens. Little oxidation occurs at V125,D150 until K216 is oxidized, suggesting that these are competitively catalyzed by the iron center; among several prolyl-4-hydroxylases the K216, H137, and D139 are conserved residues. [source] Parent,infant relationship global assessment scale: A study of its predictive validityPSYCHIATRY AND CLINICAL NEUROSCIENCES, Issue 5 2002YUTAKA AOKI Abstract The Parent,Infant Relationship Global Assessment Scale (PIRGAS; Zero to Three, 1994) provides a continuously distributed scale of infant,parent relationship adaptation, raging from ,well-adapted' to ,dangerously impaired'. The present study examines the predictive validity of the PIRGAS in a high-risk sample by coding relationship adaptation level from a single sample of 10 min of unstructured free play between mothers and their 20-month-old infants and examining its relationship to subsequent interaction with mothers and behavior problems at 24 months. Relationship adaptation assessed reliably from observations of only 10 min of free play between mothers and their infants at 20 months of age using PIRGAS predicted subsequent mother, infant interaction in a laboratory based problem-solving paradigm (Crowell procedure) at 24 months and internalizing symptomatology of Child Behavior Checklist at age 24 months. These results contribute to the predictive validity of the PIRGAS as a measure of mother,infant relationship adaptation. [source] An automated method for ,clumped-isotope' measurements on small carbonate samplesRAPID COMMUNICATIONS IN MASS SPECTROMETRY, Issue 14 2010Thomas W. Schmid Clumped-isotope geochemistry deals with the state of ordering of rare isotopes in molecules, in particular with their tendency to form bonds with other rare isotopes rather than with the most abundant ones. Among its possible applications, carbonate clumped-isotope thermometry is the one that has gained most attention because of the wide potential of applications in many disciplines of earth sciences. Clumped-isotope thermometry allows reconstructing the temperature of formation of carbonate minerals without knowing the isotopic composition of the water from which they were formed. This feature enables new approaches in paleothermometry. The currently published method is, however, limited by sample weight requirements of 10,15,mg and because measurements are performed manually. In this paper we present a new method using an automated sample preparation device coupled to an isotope ratio mass spectrometer. The method is based on the repeated analysis (n,=,6,8) of 200,µg aliquots of sample material and completely automated measurements. In addition, we propose to use precisely calibrated carbonates spanning a wide range in ,47 instead of heated gases to correct for isotope effects caused by the source of the mass spectrometer, following the principle of equal treatment of the samples and standards. We present data for international standards (NBS 19 and LSVEC) and different carbonates formed at temperatures exceeding 600°C to show that precisions in the range of 10 to 15,ppm (1 SE) can be reached for repeated analyses of a single sample. Finally, we discuss and validate the correction procedure based on high-temperature carbonates instead of heated gases. Copyright © 2010 John Wiley & Sons, Ltd. [source] Distinctiveness of macroinvertebrate communities in turloughs (temporary ponds) and their response to environmental variablesAQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS, Issue 4 2009Gwendolin Porst Abstract 1.Turloughs are a prime example of a water body type that interfaces with both the European Habitats Directive (92/43/EEC) and Water Framework Directive (2000/60/EC) (WFD), highlighting the need for an integrated strategy to protect and manage surface waters and groundwaters. To date, research on turloughs, including their invertebrate communities is limited. 2.Eight turloughs were sampled for their macroinvertebrate communities and water chemistry in April 2007. Faunal samples were collected by means of a simple box sampler. 3.Replicate samples within each turlough clustered together, indicating that a single sample can provide a meaningful description of the turlough invertebrate community. Variation of invertebrate communities within turloughs was nested among turloughs. 4.Hydroperiod influenced mean abundance and taxon richness of macroinvertebrates, but no correlation was found between nutrient status and either mean abundance or taxon richness. 5.Turloughs are priority habitats under the EC Habitats Directive, requiring maintenance of ,favourable conservation status', which needs to be assessed through monitoring, and effected through appropriate management plans. While the distinctiveness of macroinvertebrate communities across turloughs is conducive to simple and cost-effective monitoring, this also challenges the applicability of the concept of type-specific communities across these highly dynamic ecosystems. Copyright © 2009 John Wiley & Sons Ltd. [source] THE TECHNOLOGY OF PRODUCTION OF SASANIAN GLAZED POTTERY FROM VEH ARDA,?R (CENTRAL IRAQ)ARCHAEOMETRY, Issue 4 2008M. PACE Scanning electron microscopy coupled with an energy dispersive X-ray detector (SEM-EDS) has been used to study samples of Sasanian glazed pottery. Analysis of ceramic bodies revealed a general homogeneity in composition among the studied samples and the use of calcareous clay for their manufacture. Glazes are typically alkaline in composition, with sodium and potassium oxide contents between 8 and 13%, and between 3 and 5%, respectively; calcium and magnesium oxide contents are between 7 and 10%, and between 3 and 5%, respectively. These data suggest the use of plant ash together with a silica source for glaze production. Coating thickness is highly variable among different samples, from some 400 up to 1200 µm, but it is generally uniform when a single sample is concerned. Glazes are mostly coloured blue or blue-green; copper and iron are the colouring agents detected; abundance of bubbles, silicate crystals and relics of unmelted material are responsible for their generally opaque appearance, together with the presence of weathering products. The characteristics of the body to glaze contact zone, together with the widespread presence of bubbles, would not rule out production by a single firing process. A few samples feature a peculiar gritty coating on one side of their surface; SEM images show that they are actually partially vitrified, and EDS data denote a rather heterogeneous composition. It seems possible that they result from mixing clay together with the frit used for glaze development. [source] Primary cutaneous B-cell lymphoma (marginal zone) with prominent T-cell component and aberrant dual (T and B) genotype; diagnostic usefulness of laser-capture microdissectionBRITISH JOURNAL OF DERMATOLOGY, Issue 1 2006F. Gallardo Summary The presence of a dominant B- or T-cell clone is an important diagnostic criterion for distinguishing cutaneous lymphomas from lymphoid reactive infiltrates. Rarely, a combined B- and T-cell rearrangement can be detected from a single sample. In such instances, genotypic analysis does not permit differentiation of the coexistence of a T- and B-cell lymphoma from a single clone harbouring a monoclonal rearrangement for both immunoglobulin heavy chain and T-cell receptor genes. We herein report a case of a skin tumour consistent with a dense cutaneous lymphoid infiltrate showing a double prominent B- and T-cell component. A dual B- and T-cell clonality was detected by polymerase chain reaction from whole-tissue DNA sample. Genotypic analysis with DNA, obtained after laser-assisted microdissection from the B-cell population, again showed both T- and B-cell monoclonal rearrangements. Conversely, the microdissected T-cell population did not reveal a clonal pattern. The diagnosis of cutaneous B-cell lymphoma with a dual B- and T-cell genotype was established. This description illustrates the diagnostic usefulness of laser-capture microdissection in cutaneous lymphomas presenting dual genotype. [source] ORIGINAL ARTICLE: Monoclonal autoantibodies to the TSH receptor, one with stimulating activity and one with blocking activity, obtained from the same blood sampleCLINICAL ENDOCRINOLOGY, Issue 3 2010Michele Evans Summary Objective, Patients who appear to have both stimulating and blocking TSHR autoantibodies in their sera have been described, but the two activities have not been separated and analysed. We now describe the isolation and detailed characterization of a blocking type TSHR monoclonal autoantibody and a stimulating type TSHR monoclonal autoantibody from a single sample of peripheral blood lymphocytes. Design, patients and measurements, Two heterohybridoma cell lines secreting TSHR autoantibodies were isolated using standard techniques from the lymphocytes of a patient with hypothyroidism and high levels of TSHR autoantibodies (160 units/l by inhibition of TSH binding). The ability of the two new monoclonal antibodies (MAbs; K1-18 and K1-70) to bind to the TSHR and compete with TSH or TSHR antibody binding was analysed. Furthermore, the effects of K1-18 and K1-70 on cyclic AMP production in Chinese hamster ovary cells (CHO) cells expressing the TSHR were investigated. Results, One MAb (K1-18) was a strong stimulator of cyclic AMP production in TSHR-transfected CHO cells and the other (K1-70) blocked stimulation of the TSHR by TSH, K1-18, other thyroid-stimulating MAbs and patient serum stimulating type TSHR autoantibodies. Both K1-18 (IgG1 kappa) and K1-70 (IgG1 lambda) bound to the TSHR with high affinity (0·7 × 1010 l/mol and 4 × 1010 l/mol, respectively), and this binding was inhibited by unlabelled K1-18 and K1-70, other thyroid-stimulating MAbs and patient serum TSHR autoantibodies with stimulating or blocking activities. V region gene analysis indicated that K1-18 and K1-70 heavy chains used the same V region germline gene but different D and J germline genes as well as having different light chains. Consequently, the two antibodies have evolved separately from different B cell clones. Conclusions, This study provides proof that a patient can produce a mixture of blocking and stimulating TSHR autoantibodies at the same time. [source] Size-dependent species-area relationships in benthos: is the world more diverse for microbes?ECOGRAPHY, Issue 3 2002Andrey I. Azovsky Using original and literature data on species richness, I compared the species-area relations for 5 different size classes of the Arctic benthos: macrofauna sensu lato, polychaetes, nematodes, ciliates and diatom algae. The data pool covered a wide range of areas from single samples to the whole seas. Both the slopes and intercepts of the curves depended significantly on the logarithm of the mean body size of the group. The number of small species (ciliates and diatom algae) showed relatively higher local diversity but increased more slowly with the area than the number of larger ones. Thus, both ,- and ,-components of species diversity of the marine benthos were size-dependent. As a consequence, the actual relations between number of species and their physical size are spatially scale-dependent: there are many more species of smaller size classes in any one local community, but at a global scope the situation changes drastically. The possible reasons are discussed, including dispersal efficiency, rates of speciation and size-dependent perception of environmental heterogeneity. Body size is suggested to be the important scaling factor in manifestation of so-called "general ecological laws". [source] Sample pooling in 2-D gel electrophoresis: A new approach to reduce nonspecific expression backgroundELECTROPHORESIS, Issue 22 2006Marc Weinkauf Abstract Protein expression alterations unrelated to an investigated phenotype are accumulated in most cell line models during establishment. Performing a whole proteome screening of lymphoma cell lines, we established a method to reduce the influence of protein expression unrelated to the distinct investigated phenotype. In 2-D PAGE, the comprehensive analysis of a large number of protein spots would be simplified by pooling cell line samples of the investigated phenotype. Applying this pooling approach, unrelated alterations of single samples are ,muted' by dilution. Analysing two different lymphoma subtypes (follicular and mantle cell lymphoma) by this method, spots originating in only single cell lines were reduced by 72% (650/900), whereas even modestly altered expression of protein spots detected in all lines were reliably detected in the pooled protein gels. We conclude that our pooling approach is a preferable approach to reliably detect a common protein expression pattern and may even allow proteomic analysis of clinical samples with limited amounts of sample material, even with minimal cell numbers as low as 1×106. [source] Lipids and antioxidants in groats and hulls of Swedish oats (Avena sativa L)JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, Issue 6 2002Susanne Bryngelsson Abstract Concentrations and compositions of total lipids (TL), fatty acids, tocopherols and tocotrienols, avenanthramides and free hydroxycinnamic acids were determined in groats and hulls from single samples of seven Swedish oat cultivars. Total antioxidant capacity (TAC) was measured using the radical 1,1-diphenyl-2-picrylhydrazyl as substrate. Results were evaluated by principal component analysis. Consistent differences in value of the variables analysed in groats and hulls were found, groats having higher concentrations of all compounds analysed except free cinnamic acids. Concentrations of E-vitamers (especially tocotrienols) were high in both groat and hull samples with high TL. Avenanthramides were high in hull samples with high TL, but this was not found in groats. Free cinnamic acids did not follow TL in either groats or hulls. TAC was generally higher in groats than in hulls. The within-group variation in TAC was less pronounced than that in chemical composition, especially in groats. The results did not suggest any strong relationship between TAC and individual antioxidants. © 2002 Society of Chemical Industry [source] Sequence variation in the hypervariable region 1 of hepatitis C virus and posttransplantation recurrent hepatitisLIVER TRANSPLANTATION, Issue 10 2003Enrico Silini Hepatitis C virus (HCV) shows remarkable genetic variation in both populations and individuals, in whom it circulates as quasispecies (QS). Sequence variation within an infected host has adaptive significance and reflects the modes and intensity of selection mechanisms operating on the virus. We investigated the sequence diversity of hypervariable region 1 of HCV in liver transplant recipients and correlated it with the recurrence of hepatitis. Twenty-six patients were considered during a 2-year period; all had graft reinfection, and 14 patients developed hepatitis recurrence. Cloned sequences were obtained from sera collected before or within 1 month after orthotopic liver transplantation (OLT) and at 3 and 24 months thereafter. Sequence diversity within single sera and over consecutive samples was analyzed quantitatively by matrix comparison and phylogenetic analysis. Propagation of viral QS in the graft was markedly dependent on individual factors. Viral QS in post-OLT sera were less complex and evolved slower compared with immunocompetent subjects with chronic hepatitis. Sequence variation was greater during the first 3 months post-OLT than during the remaining period. Genetic diversity within single samples was not related to hepatitis recurrence or other clinical features. Conversely, sequence diversity over consecutive samples was reduced in patients who experienced hepatitis recurrence, in particular, in those infected with genotype 1b and with an HLA-DR mismatched graft. Selection of viral sequences was markedly impaired in liver transplant recipients and tended to be greater early after OLT. Reduced sequence turnover correlated negatively with the outcome of graft reinfection. [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 Bonaďti-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 naďve 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] | ||||||||||||||||||||||