ABC for Temporally Sampled Genetic Data

ABC for Temporally Sampled Genetic Dat

CodABC:A computational framework to coestimate recombination, substitution, and molecular adaptation rates by approximate bayesian computation

The estimation of substitution and recombination rates can provide important insights into the molecular evolution of protein-coding sequences. Here, we present a new computational framework, called "CodABC," to jointly estimate recombination, substitution and synonymous and nonsynonymous rates from coding data. CodABC uses approximate Bayesian computation with and without regression adjustment and implements a variety of codon models, intracodon recombination, and longitudinal sampling. CodABC can provide accurate joint parameter estimates from recombining coding sequences, often outperforming maximum-likelihood methods based on more approximate models. In addition, CodABC allows for the inclusion of several nuisance parameters such as those representing codon frequencies, transition matrices, heterogeneity across sites or invariable sites. CodABC is freely available from http://code.google.com/p/codabc/, includes a GUI, extensive documentation and ready-to-use examples, and can run in parallel on multicore machines.This work was supported by the Spanish Government with the “Juan de la Cierva” fellowship JCI-2011-10452 to M.A., the European Research Council (ERC Grant Agreement No. 617457) to D.P., and Fundac¸~ao para a Ci^encia e a Tecnologia (FCT) (grant EXCL/BIA-ANM/0549/2012) to J.S.L.Peer reviewe

Calibration and evaluation of individual-based models using Approximate Bayesian Computation

AbstractThis paper investigates the feasibility of using Approximate Bayesian Computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain.Rejection-ABC was applied to an existing 14-parameter earthworm energy budget IBM for which the available data consist of body mass growth and cocoon production in four experiments. ABC was able to narrow the posterior distributions of seven parameters, estimating credible intervals for each. ABC's accepted values produced slightly better fits than literature values do. The accuracy of the analysis was assessed using cross-validation and coverage, currently the best-available tests. Of the seven unnarrowed parameters, ABC revealed that three were correlated with other parameters, while the remaining four were found to be not estimable given the data available.It is often desirable to compare models to see whether all component modules are necessary. Here, we used ABC model selection to compare the full model with a simplified version which removed the earthworm's movement and much of the energy budget. We are able to show that inclusion of the energy budget is necessary for a good fit to the data. We show how our methodology can inform future modelling cycles, and briefly discuss how more advanced versions of ABC may be applicable to IBMs. We conclude that ABC has the potential to represent uncertainty in model structure, parameters and predictions, and to embed the often complex process of optimising an IBM's structure and parameters within an established statistical framework, thereby making the process more transparent and objective

CodABC: a computational framework to coestimate recombination, substitution, and molecular adaptation rates by approximate Bayesian computation

The estimation of substitution and recombination rates can provide important insights into the molecular evolution of protein-coding sequences. Here, we present a new computational framework, called CodABC, to jointly estimate recombination, substitution and synonymous and non-synonymous rates from coding data. CodABC uses approximate Bayesian computation (ABC) with and without regression adjustment and implements a variety of codon models, intracodon recombination and longitudinal sampling. CodABC can provide accurate joint parameter estimates from recombining coding sequences, often outperforming maximum likelihood methods based on more approximate models. In addition, CodABC allows for the inclusion of several nuisance parameters such as those representing codon frequencies, transition matrices, heterogeneity across sites or invariable sites. CodABC is freely available from http://code.google.com/p/codabc/, includes a GUI, extensive documentation and ready-touse examples, and can run in parallel on multicore machines.Ministerio de Ciencia e Innovación | Ref. JCI-2011-10452Fundação para a Ciência e a Tecnologia | Ref. EXCL/BIA-ANM/0549/201

Does Obesity Cause Thyroid Cancer? A Mendelian Randomization Study

Background: The incidence of thyroid cancer is rising, and relatively little is known about modifiable risk factors for the condition. Observational studies have suggested a link between adiposity and thyroid cancer; however, these are subject to confounding and reverse causality. Here, we used data from the UK Biobank and Mendelian randomization approaches to investigate whether adiposity causes benign nodular thyroid disease and differentiated thyroid cancer. Methods: We analyzed data from 379 708 unrelated participants of European ancestry in the UK Biobank and identified 1812 participants with benign nodular thyroid disease and 425 with differentiated thyroid carcinoma. We tested observational associations with measures of adiposity and type 2 diabetes mellitus. One and 2-sample Mendelian randomization approaches were used to investigate causal relationships. Results: Observationally, there were positive associations between higher body mass index (odds ratio [OR], 1.15; 95% confidence interval [CI], 1.08-1.22), higher waist-hip ratio (OR, 1.16; 95% CI, 1.09-1.23), and benign nodular thyroid disease, but not thyroid cancer. Mendelian randomization did not support a causal link for obesity with benign nodular thyroid disease or thyroid cancer, although it did provide some evidence that individuals in the highest quartile for genetic liability of type 2 diabetes had higher odds of thyroid cancer than those in the lowest quartile (OR, 1.45; CI, 1.11-1.90). Conclusions: Contrary to the findings of observational studies, our results do not confirm a causal role for obesity in benign nodular thyroid disease or thyroid cancer. They do, however, suggest a link between type 2 diabetes and thyroid cancer.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.WT_/Wellcome Trust/United Kingdompublished version, accepted version (12 month embargo), submitted versio

Atom efficient PtCu bimetallic catalysts and ultra dilute alloys for the selective hydrogenation of furfural

A range of Pt:Cu bimetallic nanoparticles were investigated for the liquid-phase selective hydrogenation of furfural, an important platform biomass feedstock. Alloying of the two metals had a profound effect on the overall catalytic activity, providing superior rates of reaction and achieving the needed high selectivity towards furfuryl alcohol. Furthermore, we investigated the catalytic activity of an Ultra Dilute Alloy (UDA) formed via the galvanic replacement of Cu atoms by Pt atoms on dispersed host Cu nanoparticles (atomic ratio Pt:Cu 1:20). This UDA, after overcoming an induction period, exhibits exceptionally high initial rates of hydrogenation under modest hydrogen pressures of 10 and 20 bar, rivalling the catalytic turnover for the monometallic Pt (containing 12 times more Pt), and outdoing the pure Cu or other compositions of bimetallic nanoparticle alloy catalysts. These atom efficient catalysts are ideal candidates for the valorization of furfural due to their activity and vastly greater economic viability

Telomere length and risk of idiopathic pulmonary fibrosis and chronic obstructive pulmonary disease:a mendelian randomisation study

Background: Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease accounting for 1% of UK deaths. In the familial form of pulmonary fibrosis, causal genes have been identified in about 30% of cases, and a majority of these causal genes are associated with telomere maintenance. Prematurely shortened leukocyte telomere length is associated with IPF and chronic obstructive pulmonary disease (COPD), a disease with similar demographics and shared risk factors. Using mendelian randomisation, we investigated evidence supporting a causal role for short telomeres in IPF and COPD. Methods: Mendelian randomisation inference of telomere length causality was done for IPF (up to 1369 cases) and COPD (13 538 cases) against 435 866 controls of European ancestry in UK Biobank. Polygenic risk scores were calculated and two-sample mendelian randomisation analyses were done using seven genetic variants previously associated with telomere length, with replication analysis in an IPF cohort (2668 cases vs 8591 controls) and COPD cohort (15 256 cases vs 47 936 controls). Findings: In the UK Biobank, a genetically instrumented one-SD shorter telomere length was associated with higher odds of IPF (odds ratio [OR] 4·19, 95% CI 2·33–7·55; p=0·0031) but not COPD (1·07, 0·88–1·30; p=0·51). Similarly, an association was found in the IPF replication cohort (12·3, 5·05–30·1; p=0·0015) and not in the COPD replication cohort (1·04, 0·71–1·53; p=0·83). Meta-analysis of the two-sample mendelian randomisation results provided evidence inferring that shorter telomeres cause IPF (5·81 higher odds of IPF, 95% CI 3·56–9·50; p=2·19 × 10−12). There was no evidence to infer that telomere length caused COPD (OR 1·07, 95% CI 0·90–1·27; p=0·46). Interpretation: Cellular senescence is hypothesised as a major driving force in IPF and COPD; telomere shortening might be a contributory factor in IPF, suggesting divergent mechanisms in COPD. Defining a key role for telomere shortening enables greater focus in telomere-related diagnostics, treatments, and the search for a cure in IPF. Investigation of therapies that improve telomere length is warranted. Funding: Medical Research Council.</p