Considerate Approaches to Achieving Sufficiency for ABC model selection

For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. Approximate Bayesian computation (ABC) allows us to employ the whole Bayesian formalism to problems where we can use simulations from a model, but cannot evaluate the likelihood directly. When summary statistics of real and simulated data are compared --- rather than the data directly --- information is lost, unless the summary statistics are sufficient. Here we employ an information-theoretical framework that can be used to construct (approximately) sufficient statistics by combining different statistics until the loss of information is minimized. Such sufficient sets of statistics are constructed for both parameter estimation and model selection problems. We apply our approach to a range of illustrative and real-world model selection problems

Statistical analysis of network data and evolution on GPUs: High-performance statistical computing

Network analysis typically involves as set of repetitive tasks that are particularly amenable to poor-man's parallelization. This is therefore an ideal application are for GPU architectures, which help to alleviate the tedium inherent to statistically sound analysis of network data. Here we will illustrate the use of GPUs in a range of applications, which include percolation processes on networks, the evolution of protein-protein interaction networks, and the fusion of different types of biomedical and disease data in the context of molecular interaction networks. We will pay particular attention to the numerical performance of different routines that are frequently invoked in network analysis problems. We conclude with a review over recent developments in the generation of random numbers that address the specific requirements posed by GPUs and high-performance computing needs

European sea bass (Dicentrarchus labrax) skin and scale transcriptomes

Fish skin and their appendages, the mineralized scales, are important organs for protection and homeostasis, but little is known about their specific transcript or protein repertoire. This study used RNA-seq to generate transcriptome data for skin and scales in the European sea bass (Dicentrarchus labrax), an important species for fisheries and aquaculture. RNA was extracted from the pectoral skin and from scales collected above the midline of immature one-year old sea bass. More than 20 x 10(6) reads were obtained for each tissue, using RNA-seq Illumina technology. De novo assembly resulted in 31,842 transcripts (of 500 base pairs or greater) for skin and 20,423 transcripts for scale. This dataset provides a useful resource for both aquaculture and fish conservation studies and for research into the physiology and molecular biology of fish skin and scales. (C) 2017 Elsevier B.V. All rights reserved.Foundation for Science and Technology of Portugal (FCT) [PTDC/AAG-GLO/4003/2012, CCMAR/Multi/04326/2013, SFRH/BPD/84033/2012

Transcriptome of the dead: characterisation of immune genes and marker development from necropsy samples in a free-ranging marine mammal

Background Transcriptomes are powerful resources, providing a window on the expressed portion of the genome that can be generated rapidly and at low cost for virtually any organism. However, because many genes have tissue-specific expression patterns, developing a complete transcriptome usually requires a 'discovery pool' of individuals to be sacrificed in order to harvest mRNA from as many different types of tissue as possible. This hinders transcriptome development in large, charismatic and endangered species, many of which stand the most to gain from such approaches. To circumvent this problem in a model pinniped species, we 454 sequenced cDNA from testis, heart, spleen, intestine, kidney and lung tissues obtained from nine adult male Antarctic fur seals (Arctocephalus gazella) that died of natural causes at Bird Island, South Georgia. Results After applying stringent quality control criteria based on length and annotation, we obtained 12,397 contigs which, in combination with 454 data previously obtained from skin, gave a total of 23,096 unique contigs. Homology was found to 77.0% of dog (Canis lupus familiaris) transcripts, suggesting that the combined assembly represents a substantial proportion of this species' transcriptome. Moreover, only 0.5% of transcripts revealed sequence similarity to bacteria, implying minimal contamination, and the percentage of transcripts involved in cell death was low at 2.6%. Transcripts with immune-related annotations were almost five-fold enriched relative to skin and represented 13.2% of all spleen-specific contigs. By reference to the dog, we also identified transcripts revealing homology to five class I, ten class II and three class III genes of the Major Histocompatibility Complex and derived the putative genomic distribution of 17,121 contigs, 2,119 in silico mined microsatellites and 9,382 single nucleotide polymorphisms. Conclusions Our findings suggest that transcriptome development based on samples collected post mortem may greatly facilitate genomic studies, not only of marine mammals but also more generally of species that are of conservation concern

Transcriptome of the Antarctic brooding gastropod mollusc Margarella antarctica

454 RNA-Seq transcriptome data were generated from foot tissue of the Antarctic brooding gastropod mollusc Margarella antarctica. A total of 6195 contigs were assembled de novo, providing a useful resource for researchers with an interest in Antarctic marine species, phylogenetics and mollusc biology, especially shell production

Linking saturation, stability and sustainability in food webs with observed equilibrium structure

Stability of a dynamic equilibrium in a predator-prey system depends both on the type of functional response and on the point of equilibrium on the response curve. Saturation effects from Holling type II responses are known to destabilise prey populations, while a type III (sigmoid) response curve has been shown to provide stability at lower levels of saturation. These effects have also been shown in multi-trophic model systems. However, stability analyses of observed equilibria in real complex ecosystems have as yet not assumed non-linear functional responses. Here, we evaluate the implications of saturation in observed balanced material-flow structures, for system stability and sustainability. We first make the effects of the non-linear functional responses on the interaction strengths in a food web transparent by expressing the elements of Jacobian ‘community’ matrices for type II and III systems as simple functions of their linear (type I) counterparts. We then determine the stability of the systems and distinguish two critical saturation levels: (1) a level where the system is just as stable as a type I system and (2) a level above which the system cannot be stable unless it is subsidised, separating a stable materially sustainable regime from an unsustainable one. We explain the stabilising and destabilising effects in terms of the feedbacks in the systems. The results shed light on the robustness of observed patterns of interaction strengths in complex food webs and suggest the implausibility of saturation playing a significant role in the equilibrium dynamics of sustainable ecosystems

Viterbi sparse spike detection

pre-printAccurate interpretation of seismic traveltimes and amplitudes in the exploration and global scales is complicated by the band-limited nature of seismic data. We discovered a stochastic method to reduce a seismic waveform into a most probable constituent spike train. Model waveforms were constructed from a set of candidate spike trains convolved with a source wavelet estimate. For each model waveform, a profile hidden Markov model (HMM) was constructed to represent the waveform as a stochastic generative model with a linear topology corresponding to a sequence of samples. Each match state in the HMM represented a sample in the model waveform, in which the amplitude was represented by a Gaussian distribution. Insert and delete states allowed the underlying source wavelet to dilate or contract, accounting for nonstationarity in the seismic data and errors in the source wavelet estimate. The Gaussian distribution characterizing each sample's amplitude accounted for random noise. The Viterbi algorithm was employed to simultaneously find the optimal nonlinear alignment between a model waveform and the seismic data and to assign a score to each candidate spike train. The most probable traveltimes and amplitudes were inferred from the alignments of the highest scoring models. The method required no implicit assumptions regarding the distribution of traveltimes and amplitudes; however, in practice, the solution set may be limited to mitigate the nonuniqueness of solutions and to reduce the computational effort. Our analyses found that the method can resolve closely spaced arrivals below traditional resolution limits and that traveltime estimates are robust in the presence of random noise and source wavelet errors. The method was particularly well suited to fine-scale interpretation problems such as thin bed interpretation, tying seismic images to well logs, and the analysis of anomalous waveforms in global seismology