Summary
1. Here, I present a new, multifunctional phylogenetics package, phytools, for the R statistical computing environment.

2. The focus of the package is on methods for phylogenetic comparative biology; however, it also includes tools for tree inference, phylogeny input/output, plotting, manipulation and several other tasks.

3. I describe and tabulate the major methods implemented in phytools, and in addition provide some demonstration of its use in the form of two illustrative examples.

4. Finally, I conclude by briefly describing an active web-log that I use to document present and future developments for phytools. I also note other web resources for phylogenetics in the R computational environment.

/pdf/phytools-an-r-package-for-phylogenetic-comparative-biology-yli0omoidd.pdf

phytools: an R package for phylogenetic comparative biology (and other things)

Associations between modifiable exposures and disease seen in observational epidemiology are sometimes confounded and thus misleading, despite our best efforts to improve the design and analysis of studies. Mendelian randomization-the random assortment of genes from parents to offspring that occurs during gamete formation and conception-provides one method for assessing the causal nature of some environmental exposures. The association between a disease and a polymorphism that mimics the biological link between a proposed exposure and disease is not generally susceptible to the reverse causation or confounding that may distort interpretations of conventional observational studies. Several examples where the phenotypic effects of polymorphisms are well documented provide encouraging evidence of the explanatory power of Mendelian randomization and are described. The limitations of the approach include confounding by polymorphisms in linkage disequilibrium with the polymorphism under study, that polymorphisms may have several phenotypic effects associated with disease, the lack of suitable polymorphisms for studying modifiable exposures of interest, and canalization-the buffering of the effects of genetic variation during development. Nevertheless, Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures.

/pdf/mendelian-randomization-can-genetic-epidemiology-contribute-vb0zjyrtxf.pdf

‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?

In recent months there has been an explosion of interest in using the Web to create, assemble, and disseminate geographic information provided voluntarily by individuals. Sites such as Wikimapia and OpenStreetMap are empowering citizens to create a global patchwork of geographic information, while Google Earth and other virtual globes are encouraging volunteers to develop inter- esting applications using their own data. I review this phenomenon, and examine associated issues: what drives people to do this, how accurate are the results, will they threaten individual privacy, and how can they augment more conventional sources? I compare this new phenomenon to more traditional citizen science and the role of the amateur in geographic observation.

/pdf/citizens-as-sensors-the-world-of-volunteered-geography-phibl484h3.pdf

Citizens as sensors: the world of volunteered geography

We review the recent rapid progress in the statistical physics of evolving networks. Interest has focused mainly on the structural properties of complex networks in communications, biology, social sciences and economics. A number of giant artificial networks of this kind have recently been created, which opens a wide field for the study of their topology, evolution, and the complex processes which occur in them. Such networks possess a rich set of scaling properties. A number of them are scale-free and show striking resilience against random breakdowns. In spite of the large sizes of these networks, the distances between most of their vertices are short - a feature known as the 'small-world' effect. We discuss how growing networks self-organize into scale-free structures, and investigate the role of the mechanism of preferential linking. We consider the topological and structural properties of evolving networks, and percolation and disease spread on these networks. We present a number of models demonstrat...

/pdf/evolution-of-networks-27h4ny8xbi.pdf

Evolution of networks

Yuelong Shu1, John McCauley2 1. WHO Collaborating Center for Reference and Research on Influenza, Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China 2. WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, the Francis Crick Institute, London, United Kingdom

GISAID: Global initiative on sharing all influenza data - from vision to reality.

/pdf/treetop-ecologists-brought-down-by-miners-4hzwpdd61f.pdf

Treetop ecologists brought down by miners

Critics call for restructuring of world health body, together with greater focus on fewer issues.

Declan Butler

Papers

Treetop ecologists brought down by miners

Revamp for WHO

Agent Orange health investigation stuck at square one

Open-source science takes on neglected disease

H7N9 bird flu poised to spread