Bayesian Parameter Estimation for Latent Markov Random Fields and Social Networks

Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.Comment: 26 pages, 2 figures, accepted in Journal of Computational and Graphical Statistics (http://www.amstat.org/publications/jcgs.cfm

Common Polymorphisms at the <i>CYP17A1 </i>Locus Associate With Steroid Phenotype:Support for Blood Pressure Genome-Wide Association Study Signals at This Locus

Genome-wide association studies implicate the CYP17A1 gene in human blood pressure regulation although the causative polymorphisms are as yet unknown. We sought to identify common polymorphisms likely to explain this association. We sequenced the CYP17A1 locus in 60 normotensive individuals and observed 24 previously identified single-nucleotide polymorphisms with minor allele frequency &gt;0.05. From these, we selected, for further studies, 7 polymorphisms located ≤2 kb upstream of the CYP17A1 transcription start site. In vitro reporter gene assays identified 3 of these (rs138009835, rs2150927, and rs2486758) as having significant functional effects. We then analyzed the association between the 7 polymorphisms and the urinary steroid metabolites in a hypertensive cohort (n=232). Significant associations included that of rs138009835 with aldosterone metabolite excretion; rs2150927 associated with the ratio of tetrahydrodeoxycorticosterone to tetrahydrodeoxycortisol, which we used as an index of 17α-hydroxylation. Linkage analysis showed rs138009835 to be the only 1 of the 7 polymorphisms in strong linkage disequilibrium with the blood pressure–associated polymorphisms identified in the previous studies. In conclusion, we have identified, characterized, and investigated common polymorphisms at the CYP17A1 locus that have functional effects on gene transcription in vitro and associate with corticosteroid phenotype in vivo. Of these, rs138009835—which we associate with changes in aldosterone level—is in strong linkage disequilibrium with polymorphisms linked by genome-wide association studies to blood pressure regulation. This finding clearly has implications for the development of high blood pressure in a large proportion of the population and justifies further investigation of rs138009835 and its effects

Modelling element abundances in semi-analytic models of galaxy formation

We update the treatment of chemical evolution in the Munich semi-analytic model, L-GALAXIES. Our new implementation includes delayed enrichment from stellar winds, supernovae type II (SNe-II) and supernovae type Ia (SNe-Ia), as well as metallicity-dependent yields and a reformulation of the associated supernova feedback. Two different sets of SN-II yields and three different SN-Ia delay-time distributions (DTDs) are considered, and eleven heavy elements (including O, Mg and Fe) are self-consistently tracked. We compare the results of this new implementation with data on a) local, star-forming galaxies, b) Milky Way disc G dwarfs, and c) local, elliptical galaxies. We find that the z=0 gas-phase mass-metallicity relation is very well reproduced for all forms of DTD considered, as is the [Fe/H] distribution in the Milky Way disc. The [O/Fe] distribution in the Milky Way disc is best reproduced when using a DTD with less than or equal to 50 per cent of SNe-Ia exploding within ~400 Myrs. Positive slopes in the mass-[alpha/Fe] relations of local ellipticals are also obtained when using a DTD with such a minor `prompt' component. Alternatively, metal-rich winds that drive light alpha elements directly out into the circumgalactic medium also produce positive slopes for all forms of DTD and SN-II yields considered. Overall, we find that the best model for matching the wide range of observational data considered here should include a power-law SN-Ia DTD, SN-II yields that take account of prior mass loss through stellar winds, and some direct ejection of light alpha elements out of galaxies

Prime movers : mechanochemistry of mitotic kinesins

Mitotic spindles are self-organizing protein machines that harness teams of multiple force generators to drive chromosome segregation. Kinesins are key members of these force-generating teams. Different kinesins walk directionally along dynamic microtubules, anchor, crosslink, align and sort microtubules into polarized bundles, and influence microtubule dynamics by interacting with microtubule tips. The mechanochemical mechanisms of these kinesins are specialized to enable each type to make a specific contribution to spindle self-organization and chromosome segregation

Using systems science to understand the determinants of inequities in healthy eating

Introduction: Systems thinking has emerged in recent years as a promising approach to understanding and acting on the prevention and amelioration of non-communicable disease. However, the evidence on inequities in non-communicable diseases and their risks factors, particularly diet, has not been examined from a systems perspective. We report on an approach to developing a system oriented policy actor perspective on the multiple causes of inequities in healthy eating. Methods: Collaborative conceptual modelling workshops were held in 2015 with an expert group of representatives from government, non-government health organisations and academia in Australia. The expert group built a systems model using a system dynamics theoretical perspective. The model developed from individual mind maps to pair blended maps, before being finalised as a causal loop diagram. Results: The work of the expert stakeholders generated a comprehensive causal loop diagram of the determinants of inequity in healthy eating (the HE2Diagram). This complex dynamic system has seven sub-systems: (1) food supply and environment; (2) transport; (3) housing and the built environment; (4) employment; (5) social protection; (6) health literacy; and (7) food preferences. Discussion: The HE2causal loop diagram illustrates the complexity of determinants of inequities in healthy eating. This approach, both the process of construction and the final visualisation, can provide the basis for planning the prevention and amelioration of inequities in healthy eating that engages with multiple levels of causes and existing policies and programs

Gut Microbial Gene Expression in Mother-Fed and Formula-Fed Piglets

Effects of diet on the structure and function of gut microbial communities in newborn infants are poorly understood. High-resolution molecular studies are needed to definitively ascertain whether gut microbial communities are distinct in milk-fed and formula-fed infants.Pyrosequencing-based whole transcriptome shotgun sequencing (RNA-seq) was used to evaluate community wide gut microbial gene expression in 21 day old neonatal piglets fed either with sow's milk (mother fed, MF; n = 4) or with artificial formula (formula fed, FF; n = 4). Microbial DNA and RNA were harvested from cecal contents for each animal. cDNA libraries and 16S rDNA amplicons were sequenced on the Roche 454 GS-FLX Titanium system. Communities were similar at the level of phylum but were dissimilar at the level of genus; Prevotella was the dominant genus within MF samples and Bacteroides was most abundant within FF samples. Screened cDNA sequences were assigned functional annotations by the MG-RAST annotation pipeline and based upon best-BLASTX-hits to the NCBI COG database. Patterns of gene expression were very similar in MF and FF animals. All samples were enriched with transcripts encoding enzymes for carbohydrate and protein metabolism, as well as proteins involved in stress response, binding to host epithelium, and lipopolysaccharide metabolism. Carbohydrate utilization transcripts were generally similar in both groups. The abundance of enzymes involved in several pathways related to amino acid metabolism (e.g., arginine metabolism) and oxidative stress response differed in MF and FF animals.Abundant transcripts identified in this study likely contribute to a core microbial metatranscriptome in the distal intestine. Although microbial community gene expression was generally similar in the cecal contents of MF and FF neonatal piglets, several differentially abundant gene clusters were identified. Further investigations of gut microbial gene expression will contribute to a better understanding of normal and abnormal enteric microbiology in animals and humans

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer.

BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients