Merged consensus clustering to assess and improve class discovery with microarray data

<p>Abstract</p> <p>Background</p> <p>One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a large number of methods available to perform clustering, but it is often unclear which method is best suited to the data and how to quantify the quality of the classifications produced.</p> <p>Results</p> <p>Here we describe an R package containing methods to analyse the consistency of clustering results from any number of different clustering methods using resampling statistics. These methods allow the identification of the the best supported clusters and additionally rank cluster members by their fidelity within the cluster. These metrics allow us to compare the performance of different clustering algorithms under different experimental conditions and to select those that produce the most reliable clustering structures. We show the application of this method to simulated data, canonical gene expression experiments and our own novel analysis of genes involved in the specification of the peripheral nervous system in the fruitfly, <it>Drosophila melanogaster</it>.</p> <p>Conclusions</p> <p>Our package enables users to apply the merged consensus clustering methodology conveniently within the R programming environment, providing both analysis and graphical display functions for exploring clustering approaches. It extends the basic principle of consensus clustering by allowing the merging of results between different methods to provide an averaged clustering robustness. We show that this extension is useful in correcting for the tendency of clustering algorithms to treat outliers differently within datasets. The R package, <it>clusterCons</it>, is freely available at CRAN and sourceforge under the GNU public licence.</p

The “Flexi-Chamber”: A Novel Cost-Effective In Situ Respirometry Chamber for Coral Physiological Measurements

Coral reefs are threatened worldwide, with environmental stressors increasingly affecting the ability of reef-building corals to sustain growth from calcification (G), photosynthesis (P) and respiration (R). These processes support the foundation of coral reefs by directly influencing biogeochemical nutrient cycles and complex ecological interactions and therefore represent key knowledge required for effective reef management. However, metabolic rates are not trivial to quantify and typically rely on the use of cumbersome in situ respirometry chambers and/or the need to remove material and examine ex situ, thereby fundamentally limiting the scale, resolution and possibly the accuracy of the rate data. Here we describe a novel low-cost in situ respirometry bag that mitigates many constraints of traditional glass and plexi-glass incubation chambers. We subsequently demonstrate the effectiveness of our novel "Flexi-Chamber" approach via two case studies: 1) the Flexi-Chamber provides values of P, R and G for the reef-building coral Siderastrea cf. stellata collected from reefs close to Salvador, Brazil, which were statistically similar to values collected from a traditional glass respirometry vessel; and 2) wide-scale application of obtaining P, R and G rates for different species across different habitats to obtain inter- and intra-species differences. Our novel cost-effective design allows us to increase sampling scale of metabolic rate measurements in situ without the need for destructive sampling and thus significantly expands on existing research potential, not only for corals as we have demonstrated here, but also other important benthic groups

ELAC2 polymorphisms and prostate cancer risk: a meta-analysis based on 18 case–control studies

Polymorphisms in the elaC homolog-2 (ELAC2)/HPC2 gene have been hypothesized to alter the risk of prostate cancer. However, the results of the related published studies remained conflicting. We performed a meta-analysis of 18 studies evaluating the association between ELAC2 Ser217Leu and Ala541Thr polymorphisms and prostate cancer risk. Overall, ELAC2 Leu217 allele was associated with increased prostate cancer risk as compared with the Ser217 allele (odds ratio (OR)=1.13, 95% confidence interval (CI): 1.03–1.24, P=0.019 for heterogeneity), as well as in the heterozygote comparison (OR=1.21, 95% CI: 1.07–1.36, P=0.034 for heterogeneity) and the dominant genetic model (OR=1.20, 95% CI: 1.07–1.35, P=0.025 for heterogeneity). Furthermore, the ELAC2 Thr541 allele was associated with increased prostate cancer risk as compared with the Ala541 allele (OR=1.22, 95% CI: 1.00–0.48, P=0.131 for heterogeneity). In the stratified analyses for Ser217Leu polymorphism, there was significantly increased prostate cancer risk in Asian and Caucasian populations, and studies using sporadic and familial prostate cancer cases. Similar result was found in the Asian population in the stratified analyses for Ala541Thr polymorphism. This meta-analysis showed evidence that ELAC2 Ser217Leu and Ala541Thr polymorphisms were associated with prostate cancer risk, and might be low-penetrance susceptibility markers of prostate cancer

The methanol dehydrogenase gene, mxaF, as a functional and phylogenetic marker for proteobacterial methanotrophs in natural environments

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS ONE 8 (2013): e56993, doi:10.1371/journal.pone.0056993.The mxaF gene, coding for the large (α) subunit of methanol dehydrogenase, is highly conserved among distantly related methylotrophic species in the Alpha-, Beta- and Gammaproteobacteria. It is ubiquitous in methanotrophs, in contrast to other methanotroph-specific genes such as the pmoA and mmoX genes, which are absent in some methanotrophic proteobacterial genera. This study examined the potential for using the mxaF gene as a functional and phylogenetic marker for methanotrophs. mxaF and 16S rRNA gene phylogenies were constructed based on over 100 database sequences of known proteobacterial methanotrophs and other methylotrophs to assess their evolutionary histories. Topology tests revealed that mxaF and 16S rDNA genes of methanotrophs do not show congruent evolutionary histories, with incongruencies in methanotrophic taxa in the Methylococcaceae, Methylocystaceae, and Beijerinckiacea. However, known methanotrophs generally formed coherent clades based on mxaF gene sequences, allowing for phylogenetic discrimination of major taxa. This feature highlights the mxaF gene’s usefulness as a biomarker in studying the molecular diversity of proteobacterial methanotrophs in nature. To verify this, PCR-directed assays targeting this gene were used to detect novel methanotrophs from diverse environments including soil, peatland, hydrothermal vent mussel tissues, and methanotroph isolates. The placement of the majority of environmental mxaF gene sequences in distinct methanotroph-specific clades (Methylocystaceae and Methylococcaceae) detected in this study supports the use of mxaF as a biomarker for methanotrophic proteobacteria.This work was supported in part by grants from the U.S. National Science Foundation Ecosystems Studies program (awards # DEB9708092 and DEB0089738)

Alterations in ethanol-induced behaviors and consumption in knock-in mice expressing ethanol-resistant NMDA receptors

Ethanol's action on the brain likely reflects altered function of key ion channels such as glutamatergic N-methyl-D-aspartate receptors (NMDARs). In this study, we determined how expression of a mutant GluN1 subunit (F639A) that reduces ethanol inhibition of NMDARs affects ethanol-induced behaviors in mice. Mice homozygous for the F639A allele died prematurely while heterozygous knock-in mice grew and bred normally. Ethanol (44 mM; ∼0.2 g/dl) significantly inhibited NMDA-mediated EPSCs in wild-type mice but had little effect on responses in knock-in mice. Knock-in mice had normal expression of GluN1 and GluN2B protein across different brain regions and a small reduction in levels of GluN2A in medial prefrontal cortex. Ethanol (0.75-2.0 g/kg; IP) increased locomotor activity in wild-type mice but had no effect on knock-in mice while MK-801 enhanced activity to the same extent in both groups. Ethanol (2.0 g/kg) reduced rotarod performance equally in both groups but knock-in mice recovered faster following a higher dose (2.5 g/kg). In the elevated zero maze, knock-in mice had a blunted anxiolytic response to ethanol (1.25 g/kg) as compared to wild-type animals. No differences were noted between wild-type and knock-in mice for ethanol-induced loss of righting reflex, sleep time, hypothermia or ethanol metabolism. Knock-in mice consumed less ethanol than wild-type mice during daily limited-access sessions but drank more in an intermittent 24 h access paradigm with no change in taste reactivity or conditioned taste aversion. Overall, these data support the hypothesis that NMDA receptors are important in regulating a specific constellation of effects following exposure to ethanol. © 2013 den Hartog et al

A Nomenclature for Vertebral Fossae in Sauropods and Other Saurischian Dinosaurs

The axial skeleton of extinct saurischian dinosaurs (i.e., theropods, sauropodomorphs), like living birds, was pneumatized by epithelial outpocketings of the respiratory system. Pneumatic signatures in the vertebral column of fossil saurischians include complex branching chambers within the bone (internal pneumaticity) and large chambers visible externally that are bounded by neural arch laminae (external pneumaticity). Although general aspects of internal pneumaticity are synapomorphic for saurischian subgroups, the individual internal pneumatic spaces cannot be homologized across species or even along the vertebral column, due to their variability and absence of topographical landmarks. External pneumatic structures, in contrast, are defined by ready topological landmarks (vertebral laminae), but no consistent nomenclatural system exists. This deficiency has fostered confusion and limited their use as character data in phylogenetic analysis.We present a simple system for naming external neural arch fossae that parallels the one developed for the vertebral laminae that bound them. The nomenclatural system identifies fossae by pointing to reference landmarks (e.g., neural spine, centrum, costal articulations, zygapophyses). We standardize the naming process by creating tripartite names from “primary landmarks,” which form the zygodiapophyseal table, “secondary landmarks,” which orient with respect to that table, and “tertiary landmarks,” which further delineate a given fossa.The proposed nomenclatural system for lamina-bounded fossae adds clarity to descriptions of complex vertebrae and allows these structures to be sourced as character data for phylogenetic analyses. These anatomical terms denote potentially homologous pneumatic structures within Saurischia, but they could be applied to any vertebrate with vertebral laminae that enclose spaces, regardless of their developmental origin or phylogenetic distribution

Changes in the nanoparticle aggregation rate due to the additional effect of electrostatic and magnetic forces on mass transport coefficients

The need may arise to be able to simulate the migration of groundwater nanoparticles through the ground. Transportation velocities of nanoparticles are different from that of water and depend on many processes that occur during migration. Unstable nanoparticles, such as zero-valent iron nanoparticles, are especially slowed down by aggregation between them. The aggregation occurs when attracting forces outweigh repulsive forces between the particles. In the case of iron nanoparticles that are used for remediation, magnetic forces between particles contribute to attractive forces and nanoparticles aggregate rapidly. This paper describes the addition of attractive magnetic forces and repulsive electrostatic forces between particles (by 'particle', we mean both single nanoparticles and created aggregates) into a basic model of aggregation which is commonly used. This model is created on the basis of the flow of particles in the proximity of observed particles that gives the rate of aggregation of the observed particle. By using a limit distance that has been described in our previous work, the flow of particles around one particle is observed in larger spacing between the particles. Attractive magnetic forces between particles draw the particles into closer proximity and result in aggregation. This model fits more closely with rapid aggregation which occurs between magnetic nanoparticles.Ministry of Education of the Czech Republic of the Technical University in Liberec [7822]; Ministry of Education of the Czech Republic [FR-TI1/456]; Ministry of Industry and Trad