Publisher Correction: Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Corallopyronin A: antimicrobial discovery to preclinical development.

Covering: August 1984 up to January 2022Worldwide, increasing morbidity and mortality due to antibiotic-resistant microbial infections has been observed. Therefore, better prevention and control of infectious diseases, as well as appropriate use of approved antibacterial drugs are crucial. There is also an urgent need for the continuous development and supply of novel antibiotics. Thus, identifying new antibiotics and their further development is once again a priority of natural product research. The antibiotic corallopyronin A was discovered in the 1980s in the culture broth of the Myxobacterium Corallococcus coralloides and serves, in the context of this review, as a show case for the development of a naturally occurring antibiotic compound. The review demonstrates how a hard to obtain, barely water soluble and unstable compound such as corallopyronin A can be developed making use of sophisticated production and formulation approaches. Corallopyronin A is a bacterial DNA-dependent RNA polymerase inhibitor with a new target site and one of the few representatives of this class currently in preclinical development. Efficacy against Gram-positive and Gram-negative pathogens, e.g., Chlamydia trachomatis, Orientia tsutsugamushi, Staphylococcus aureus, and Wolbachia has been demonstrated. Due to its highly effective in vivo depletion of Wolbachia, which are essential endobacteria of most filarial nematode species, and its robust macrofilaricidal efficacy, corallopyronin A was selected as a preclinical candidate for the treatment of human filarial infections. This review highlights the discovery and production optimization approaches for corallopyronin A, as well as, recent preclinical efficacy results demonstrating a robust macrofilaricidal effect of the anti-Wolbachia candidate, and the solid formulation strategy which enhances the stability as well as the bioavailability of corallopyronin A.

Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl.

Segmenting the nuclei of cells in microscopy images is often the first step in the quantitative analysis of imaging data for biological and biomedical applications. Many bioimage analysis tools can segment nuclei in images but need to be selected and configured for every experiment. The 2018 Data Science Bowl attracted 3,891 teams worldwide to make the first attempt to build a segmentation method that could be applied to any two-dimensional light microscopy image of stained nuclei across experiments, with no human interaction. Top participants in the challenge succeeded in this task, developing deep-learning-based models that identified cell nuclei across many image types and experimental conditions without the need to manually adjust segmentation parameters. This represents an important step toward configuration-free bioimage analysis software tools.

Assessment of significance of conditionally independent GWAS signals.

MOTIVATION: Multiple independently associated SNPs within a linkage disequilibrium region are a common phenomenon. Conditional analysis has been successful in identifying secondary signals. While conditional association tests are limited to specific genomic regions, they are benchmarked with genome-wide scale criterion, a conservative strategy. Within the weighted hypothesis testing framework, we developed a 'quasi-adaptive' method that uses the pairwise correlation (r2) and physical distance (d) from the index association to construct priority functions G =G(r2, d), which assign an SNP-specific α-threshold to each SNP. Family-wise error rate (FWER) and power of the approach were evaluated via simulations based on real GWAS data. We compared a series of different G-functions. RESULTS: Simulations under the null hypothesis on 1,100 primary SNPs confirmed appropriate empirical FWER for all G-functions. A G-function with optimal r2 = 0.3 between index and secondary SNP which down-weighted SNPs at higher distance step-wise-strong and gave more emphasis on d than on r2 had overall best power. It also gave the best results in application to the real datasets. As a proof of concept, 'quasi-adaptive' method was applied to GWAS on free thyroxine (FT4), inflammatory bowel disease (IBD) and human height. Application of the algorithm revealed 5 secondary signals in our example GWAS on FT4, 5 secondary signals in case of the IBD and 19 secondary signals on human height, that would have gone undetected with the established genome-wide threshold (α=5×10-8). AVAILABILITY AND IMPLEMENTATION: https://github.com/sghasemi64/Secondary-Signal. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Using item response theory to appraise key feature examinations for clinical reasoning.

BACKGROUND: Validation of examinations is usually based on classical test theory. In this study, we analysed a key feature examination according to item response theory and compared the results with those of a classical test theory approach. METHODS: Over the course of five years, 805 fourth-year undergraduate students took a key feature examination on general medicine consisting of 30 items. Analyses were run according to a classical test theory approach as well as using item response theory. Classical test theory analyses are reported as item difficulty, discriminatory power, and Cronbach's alpha while item response theory analyses are presented as item characteristics curves, item information curves and a test information function. RESULTS: According to classical test theory findings, the examination was labelled as easy. Analyses according to item response theory more specifically indicated that the examination was most suited to identify struggling students. Furthermore, the analysis allowed for adapting the examination to specific ability ranges by removing items, as well as comparing multiple samples with varying ability ranges. CONCLUSIONS: Item response theory analyses revealed results not yielded by classical test theory. Thus, both approaches should be routinely combined to increase the information yield of examination data.

Deep Learning-based Propensity Scores for Confounding Control in Comparative Effectiveness Research: A Large-scale, Real-world Data Study.

BACKGROUND: Due to the non-randomized nature of real-world data, prognostic factors need to be balanced, which is often done by propensity scores (PSs). This study aimed to investigate whether autoencoders, which are unsupervised deep learning architectures, might be leveraged to compute PS. METHODS: We selected patient-level data of 128,368 first-line treated cancer patients from the Flatiron Health EHR-derived de-identified database. We trained an autoencoder architecture to learn a lower-dimensional patient representation, which we used to compute PS. To compare the performance of an autoencoder-based PS with established methods, we performed a simulation study. We assessed the balancing and adjustment performance using standardized mean differences, root mean square errors (RMSE), percent bias, and confidence interval coverage. To illustrate the application of the autoencoder-based PS, we emulated the PRONOUNCE trial by applying the trial's protocol elements within an observational database setting, comparing two chemotherapy regimens. RESULTS: All methods but the manual variable selection approach led to well-balanced cohorts with average standardized mean differences <0.1. LASSO yielded on average the lowest deviation of resulting estimates (RMSE 0.0205) followed by the autoencoder approach (RMSE 0.0248). Altering the hyperparameter setup in sensitivity analysis, the autoencoder approach led to similar results as LASSO (RMSE 0.0203 and 0.0205, respectively). In the case study, all methods provided a similar conclusion with point estimates clustered around the null (e.g., HRautoencoder 1.01 [95% confidence interval = 0.80, 1.27] vs. HRPRONOUNCE 1.07 [0.83, 1.36]). CONCLUSIONS: Autoencoder-based PS computation was a feasible approach to control for confounding but did not perform better than some established approaches like LASSO.

CellProfiler 3.0: Next-generation image processing for biology.

CellProfiler has enabled the scientific research community to create flexible, modular image analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new version of the software supporting both whole-volume and plane-wise analysis of three-dimensional (3D) image stacks, increasingly common in biomedical research. CellProfiler's infrastructure is greatly improved, and we provide a protocol for cloud-based, large-scale image processing. New plugins enable running pretrained deep learning models on images. Designed by and for biologists, CellProfiler equips researchers with powerful computational tools via a well-documented user interface, empowering biologists in all fields to create quantitative, reproducible image analysis workflows.

Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images.

Identifying nuclei is often a critical first step in analyzing microscopy images of cells and classical image processing algorithms are most commonly used for this task. Recent developments in deep learning can yield superior accuracy, but typical evaluation metrics for nucleus segmentation do not satisfactorily capture error modes that are relevant in cellular images. We present an evaluation framework to measure accuracy, types of errors, and computational efficiency; and use it to compare deep learning strategies and classical approaches. We publicly release a set of 23,165 manually annotated nuclei and source code to reproduce experiments and run the proposed evaluation methodology. Our evaluation framework shows that deep learning improves accuracy and can reduce the number of biologically relevant errors by half. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

OCTP: A Tool for On-the-Fly Calculation of Transport Properties of Fluids with the Order- n Algorithm in LAMMPS.

We present a new plugin for LAMMPS for on-the-fly computation of transport properties (OCTP) in equilibrium molecular dynamics. OCTP computes the self- and Maxwell-Stefan diffusivities, bulk and shear viscosities, and thermal conductivities of pure fluids and mixtures in a single simulation. OCTP is the first implementation in LAMMPS that uses the Einstein relations combined with the order- n algorithm for the efficient sampling of dynamic variables. OCTP has low computational requirements and is easy to use because it follows the native input file format of LAMMPS. A tool for calculating the radial distribution function (RDF) of the fluid beyond the cutoff radius, while taking into account the system size effects, is also part of the new plugin. The RDFs computed from OCTP are needed to obtain the thermodynamic factor, which relates Maxwell-Stefan and Fick diffusivities. To demonstrate the efficiency of the new plugin, the transport properties of an equimolar mixture of water-methanol were computed at 298 K and 1 bar.

Tumstatin fragment selectively inhibits neutrophil infiltration in experimental asthma exacerbation.

BACKGROUND: Asthma is a chronic inflammatory disease with structural changes present. Burgess and colleagues recently found tumstatin markedly reduced in adult asthmatic lung tissue compared with nonasthmatics. ECM fragments such as tumstatin are named matrikines and act independently of the parent molecule. The role of Col IV matrikines in neutrophil inflammation (eg. exacerbation in asthma) has not been investigated to date. Severe adult asthma phenotypes are dominated by neutrophilic inflammation and show a high frequency of severe exacerbations. OBJECTIVE: This study sought to investigate the role of a novel active region within tumstatin (CP17) and its implication in neutrophil inflammatory responses related to asthma exacerbation. METHODS: For reactive oxygen production, isolated neutrophils were preincubated with peptides or vehicle for 1 hour and stimulated (PMA). Luminescence signal was recorded (integration over 10 seconds) for 1.5 hours. Neutrophil migration was performed according to the SiMA protocol. Mice were sensitized to OVA/Alumn by intraperitoneal (i.p.) injections. Mice were then treated with CP17, vehicle (PBS) or scrambled peptide (SP17) after OVA exposure (days 27 and 28, polyI:C stimulation). All animals were killed on day 29 with lung function measurement, histology and lavage. RESULTS: CP17 decreased total ROS production rate to 52.44% (0.5 µmol/L, P < 0.05 vs SP17), reduced the in vitro directionality (vs SP17, P = 1 × 10-6 ) and migration speed (5 µmol/L, P = 1 × 10-3 ). In vivo application of CP17 decreased neutrophil inflammation ~1.8-fold (P < 0.001 vs SP17) and reduced numbers of mucus-producing cells (-29%, P < 0.05). CONCLUSION: CP17 reduced the ROS production rate, migrational speed and selectively inhibited neutrophil accumulation in the lung interstitium and lumen. CLINICAL RELEVANCE: CP17 may serve as a potential precursor for drug development to combat overwhelming neutrophil inflammation.

Single nucleotide polymorphisms in the angiogenic and lymphangiogenic pathways are associated with lymphedema caused by Wuchereria bancrofti.

BACKGROUND: Lymphedema (LE) is a chronic clinical manifestation of filarial nematode infections characterized by lymphatic dysfunction and subsequent accumulation of protein-rich fluid in the interstitial space-lymphatic filariasis. A number of studies have identified single nucleotide polymorphisms (SNPs) associated with primary and secondary LE. To assess SNPs associated with LE caused by lymphatic filariasis, a cross-sectional study of unrelated Ghanaian volunteers was designed to genotype SNPs in 285 LE patients as cases and 682 infected patients without pathology as controls. One hundred thirty-one SNPs in 64 genes were genotyped. The genes were selected based on their roles in inflammatory processes, angiogenesis/lymphangiogenesis, and cell differentiation during tumorigenesis. RESULTS: Genetic associations with nominal significance were identified for five SNPs in three genes: vascular endothelial growth factor receptor-3 (VEGFR-3) rs75614493, two SNPs in matrix metalloprotease-2 (MMP-2) rs1030868 and rs2241145, and two SNPs in carcinoembryonic antigen-related cell adhesion molecule-1 (CEACAM-1) rs8110904 and rs8111171. Pathway analysis revealed an interplay of genes in the angiogenic/lymphangiogenic pathways. Plasma levels of both MMP-2 and CEACAM-1 were significantly higher in LE cases compared to controls. Functional characterization of the associated SNPs identified genotype GG of CEACAM-1 as the variant influencing the expression of plasma concentration, a novel finding observed in this study. CONCLUSION: The SNP associations found in the MMP-2, CEACAM-1, and VEGFR-3 genes indicate that angiogenic/lymphangiogenic pathways are important in LE clinical development.

Potential of polarizable force fields for predicting the separation performance of small hydrocarbons in M-MOF-74.

The separation of light olefins from paraffins via cryogenic distillation is a very energy intensive process. Solid adsorbents and especially metal-organic frameworks with open metal sites have the potential to significantly lower the required energy. Specifically, M-MOF-74 has drawn considerable attention for application in olefin/paraffin separation. To investigate how the separation proceeds on a molecular level and to design better materials, molecular simulation can be a useful tool. Unfortunately, it is still a challenge to model the adsorption behavior of many adsorbates in metal-organic frameworks with open metal sites. Previously, the inclusion of explicit polarization has been suggested to improve the quality of classical force fields for such systems. Here, the potential of polarizable force fields for the description of olefins and paraffins in metal-organic frameworks with open metal sites is investigated. In particular, heats of adsorption, binding geometries, and adsorption isotherms are calculated for C2H4, C2H6, C3H6, and C3H8 in M-MOF-74 (with M = Co, Mn, Fe, and Ni). In this study, no force field parameters are adjusted to improve the model. The results show that including explicit polarization significantly improves the description of the adsorption in comparison to non-polarizable generic force fields which do not consider explicit polarization. The study also reveals that simulation predictions are sensitive to the assigned repulsive potential and framework charges. A fully re-parametrized polarizable force field may have the capability to improve the predictions even further.

Tumstatin regulates the angiogenic and inflammatory potential of airway smooth muscle extracellular matrix.

The extracellular matrix (ECM) creates the microenvironment of the tissue; an altered ECM in the asthmatic airway may be central in airway inflammation and remodelling. Tumstatin is a collagen IV-derived matrikine reduced in the asthmatic airway wall that reverses airway inflammation and remodelling in small and large animal models of asthma. This study hypothesized that the mechanisms underlying the broad asthma-resolving effects of tumstatin were due to autocrine remodelling of the ECM. Neutrophils and endothelial cells were seeded on decellularized ECM of non-asthmatic (NA) or asthmatic (A) airway smooth muscle (ASM) cells previously exposed to tumstatin in the presence or absence of a broad matrix metalloproteinase inhibitor, Marimastat. Gene expression in NA and A ASM induced by tumstatin was assessed using RT-PCR arrays. The presence of tumstatin during ECM deposition affected neutrophil and endothelial cell properties on both NA and A ASM-derived matrices and this was only partly due to MMP activity. Gene expression patterns in response to tumstatin in NA and A ASM cells were different. Tumstatin may foster an anti-inflammatory and anti-angiogenic microenvironment by modifying ASM-derived ECM. Further work is required to examine whether restoring tumstatin levels in the asthmatic airway represents a potential novel therapeutic approach.

Haplotype synthesis analysis reveals functional variants underlying known genome-wide associated susceptibility loci.

MOTIVATION: The functional mechanisms underlying disease association remain unknown for Genome-wide Association Studies (GWAS) susceptibility variants located outside coding regions. Synthesis of effects from multiple surrounding functional variants has been suggested as an explanation of hard-to-interpret findings. We define filter criteria based on linkage disequilibrium measures and allele frequencies which reflect expected properties of synthesizing variant sets. For eligible candidate sets, we search for haplotype markers that are highly correlated with associated variants. RESULTS: Via simulations we assess the performance of our approach and suggest parameter settings which guarantee 95% sensitivity at 20-fold reduced computational cost. We apply our method to 1000 Genomes data and confirmed Crohn's Disease (CD) and Type 2 Diabetes (T2D) variants. A proportion of 36.9% allowed explanation by three-variant-haplotypes carrying at least two functional variants, as compared to 16.4% for random variants ([Formula: see text]). Association could be explained by missense variants for MUC19, PER3 (CD) and HMG20A (T2D). In a CD GWAS-imputed using haplotype reference consortium data (64 976 haplotypes)-we could confirm the syntheses of MUC19 and PER3 and identified synthesis by missense variants for 6 further genes (ZGPAZ, GPR65, CLN3/NPIPB8, LOC102723878, rs2872507, GCKR). In all instances, the odds ratios of the synthesizing haplotypes were virtually identical to that of the index SNP. In summary, we demonstrate the potential of synthesis analysis to guide functional follow-up of GWAS findings. AVAILABILITY AND IMPLEMENTATION: All methods are implemented in the C/C ++ toolkit GetSynth, available at http://sourceforge.net/projects/getsynth/ CONTACT: tim.becker@uni-greifswald.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SiMA: A simplified migration assay for analyzing neutrophil migration.

In lung inflammation, neutrophils are the first leukocytes migrating to an inflammatory site, eliminating pathogens by multiple mechanisms. The term "migration" describes several stages of neutrophil movement to reach the site of inflammation, of which the passage of the interstitium and basal membrane of the airway are necessary to reach the site of bronchial inflammation. Currently, several methods exist (e.g., Boyden Chamber, under-agarose assay, or microfluidic systems) to assess neutrophil mobility. However, these methods do not allow for parameterization on single cell level, that is, the individual neutrophil pathway analysis is still considered challenging. This study sought to develop a simplified yet flexible method to monitor and quantify neutrophil chemotaxis by utilizing commercially available tissue culture hardware, simple video microscopic equipment and highly standardized tracking. A chemotaxis 3D µ-slide (IBIDI) was used with different chemoattractants [interleukin-8 (IL-8), fMLP, and Leukotriene B4 (LTB4 )] to attract neutrophils in different matrices like Fibronectin (FN) or human placental matrix. Migration was recorded for 60 min using phase contrast microscopy with an EVOS® FL Cell Imaging System. The images were normalized and texture based image segmentation was used to generate neutrophil trajectories. Based on these spatio-temporal information a comprehensive parameter set is extracted from each time series describing the neutrophils motility, including velocity and directness and neutrophil chemotaxis. To characterize the latter one, a sector analysis was employed enabling the quantification of the neutrophils response to the chemoattractant. Using this hard- and software framework we were able to identify typical migration profiles of the chemoattractants IL-8, fMLP, and LTB4 , the effect of the matrices FN versus HEM as well as the response to different medications (Prednisolone). Additionally, a comparison of four asthmatic and three non-asthmatic patients gives a first hint to the capability of SiMA assay in the context of migration based diagnostics. Using SiMA we were able to identify typical migration profiles of the chemoattractants IL-8, fMLP, and LTB4 , the effect of the matrices FN versus HEM as well as the response to different medications, that is, Prednisolone induced a change of direction of migrating neutrophils in FN but no such effect was observed in human placental matrix. In addition, neutrophils of asthmatic individuals showed an increased proportion of cells migrating toward the vehicle. With the SiMA platform we presented a simplified but yet flexible platform for cost-effective tracking and quantification of neutrophil migration. The introduced method is based on a simple microscopic video stage, standardized, commercially available, µ-fluidic migration chambers and automated image analysis, and track validation software. © 2017 International Society for Advancement of Cytometry.

Low-level APC mutational mosaicism is the underlying cause in a substantial fraction of unexplained colorectal adenomatous polyposis cases.

BACKGROUND: In 30-50% of patients with colorectal adenomatous polyposis, no germline mutation in the known genes APC, causing familial adenomatous polyposis, MUTYH, causing MUTYH-associated polyposis, or POLE or POLD1, causing polymerase-proofreading-associated polyposis can be identified, although a hereditary aetiology is likely. This study aimed to explore the impact of APC mutational mosaicism in unexplained polyposis. METHODS: To comprehensively screen for somatic low-level APC mosaicism, high-coverage next-generation sequencing of the APC gene was performed using DNA from leucocytes and a total of 53 colorectal tumours from 20 unrelated patients with unexplained sporadic adenomatous polyposis. APC mosaicism was assumed if the same loss-of-function APC mutation was present in ≥ 2 anatomically separated colorectal adenomas/carcinomas per patient. All mutations were validated using diverse methods. RESULTS: In 25% (5/20) of patients, somatic mosaicism of a pathogenic APC mutation was identified as underlying cause of the disease. In 2/5 cases, the mosaic level in leucocyte DNA was slightly below the sensitivity threshold of Sanger sequencing; while in 3/5 cases, the allelic fraction was either very low (0.1-1%) or no mutations were detectable. The majority of mosaic mutations were located outside the somatic mutation cluster region of the gene. CONCLUSIONS: The present data indicate a high prevalence of pathogenic mosaic APC mutations below the detection thresholds of routine diagnostics in adenomatous polyposis, even if high-coverage sequencing of leucocyte DNA alone is taken into account. This has important implications for both routine work-up and strategies to identify new causative genes in this patient group.

Intersession Reliability of Isokinetic Strength Testing in Knee and Elbow Extension and Flexion Using the BTE PrimusRS.

CONTEXT: The use of isokinetic dynamometers playing an important role in different settings of sports and medicine. Therefore, a high reliability of these devices is required. OBJECTIVE: The aim of this study was to examine the intersession reliability of the dynamometer BTE PrimusRS regarding to the isolated single-joint exercises extension/flexion of the knee and elbow for isokinetic testing DESIGN: Intersession reliability. SETTING: Clinical settings and sports science. PARTICIPANTS: 16 young male students. INTERVENTION: The testing protocol includes 5 consecutive repetitions (concentric/concentric) at a velocity of 60°/s for the exercises. MAIN OUTCOME MEASURES: Raw data of torque curves were used to determine the peak torque. Reliability was evaluated with the intraclass correlation coefficient (ICC), the limits of agreement (LoA), and the bias and the variability of measurements (V). RESULTS: High ICC values (.954-.991) were found for the used exercises. However, the LoAs yielded up to over 16 Nm and the V yielded up to nearly 9 % in several testing exercises, indicating poor absolute reliability. CONCLUSION: The BTE PrimusRS shows good to excellent reliability. However, regarding the absolute measures of reliability, the users must decide as experts in their fields whether this reliability is sufficient for their purposes.

SUCLG2 identified as both a determinator of CSF Aß1-42 levels and an attenuator of cognitive decline in Alzheimer's disease.

Cerebrospinal fluid amyloid-beta 1-42 (Aß1-42) and phosphorylated Tau at position 181 (pTau181) are biomarkers of Alzheimer's disease (AD). We performed an analysis and meta-analysis of genome-wide association study data on Aß1-42 and pTau181 in AD dementia patients followed by independent replication. An association was found between Aß1-42 level and a single-nucleotide polymorphism in SUCLG2 (rs62256378) (P = 2.5×10(-12)). An interaction between APOE genotype and rs62256378 was detected (P = 9.5 × 10(-5)), with the strongest effect being observed in APOE-ε4 noncarriers. Clinically, rs62256378 was associated with rate of cognitive decline in AD dementia patients (P = 3.1 × 10(-3)). Functional microglia experiments showed that SUCLG2 was involved in clearance of Aß1-42.

Genome-wide association study and mouse expression data identify a highly conserved 32 kb intergenic region between WNT3 and WNT9b as possible susceptibility locus for isolated classic exstrophy of the bladder.

Bladder exstrophy-epispadias complex (BEEC), the severe end of the urorectal malformation spectrum, has a profound impact on continence as well as sexual and renal functions. It is widely accepted that for the majority of cases the genetic basis appears to be multifactorial. Here, we report the first study which utilizes genome-wide association methods to analyze a cohort comprising patients presenting the most common BEEC form, classic bladder exstrophy (CBE), to identify common variation associated with risk for isolated CBE. We employed discovery and follow-up samples comprising 218 cases/865 controls and 78 trios in total, all of European descent. Our discovery sample identified a marker near SALL1, showing genome-wide significant association with CBE. However, analyses performed on follow-up samples did not add further support to these findings. We were also able to identify an association with CBE across our study samples (discovery: P = 8.88 × 10(-5); follow-up: P = 0.0025; combined: 1.09 × 10(-6)) in a highly conserved 32 kb intergenic region containing regulatory elements between WNT3 and WNT9B. Subsequent analyses in mice revealed expression for both genes in the genital region during stages relevant to the development of CBE in humans. Unfortunately, we were not able to replicate the suggestive signal for WNT3 and WNT9B in a sample that was enriched for non-CBE BEEC cases (P = 0.51). Our suggestive findings support the hypothesis that larger samples are warranted to identify association of common variation with CBE.

METAINTER: meta-analysis of multiple regression models in genome-wide association studies.

MOTIVATION: Meta-analysis of summary statistics is an essential approach to guarantee the success of genome-wide association studies (GWAS). Application of the fixed or random effects model to single-marker association tests is a standard practice. More complex methods of meta-analysis involving multiple parameters have not been used frequently, a gap that could be explained by the lack of a respective meta-analysis pipeline. Meta-analysis based on combining p-values can be applied to any association test. However, to be powerful, meta-analysis methods for high-dimensional models should incorporate additional information such as study-specific properties of parameter estimates, their effect directions, standard errors and covariance structure. RESULTS: We modified 'method for the synthesis of linear regression slopes' recently proposed in the educational sciences to the case of multiple logistic regression, and implemented it in a meta-analysis tool called METAINTER. The software handles models with an arbitrary number of parameters, and can directly be applied to analyze the results of single-SNP tests, global haplotype tests, tests for and under gene-gene or gene-environment interaction. Via simulations for two-single nucleotide polymorphisms (SNP) models we have shown that the proposed meta-analysis method has correct type I error rate. Moreover, power estimates come close to that of the joint analysis of the entire sample. We conducted a real data analysis of six GWAS of type 2 diabetes, available from dbGaP (http://www.ncbi.nlm.nih.gov/gap). For each study, a genome-wide interaction analysis of all SNP pairs was performed by logistic regression tests. The results were then meta-analyzed with METAINTER. AVAILABILITY: The software is freely available and distributed under the conditions specified on http://metainter.meb.uni-bonn.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.