Copy Number Variants in German Patients with Schizophrenia

Large rare copy number variants (CNVs) have been recognized as significant genetic risk factors for the development of schizophrenia (SCZ). However, due to their low frequency (1∶150 to 1∶1000) among patients, large sample sizes are needed to detect an association between specific CNVs and SCZ. So far, the majority of genome-wide CNV analyses have focused on reporting only CNVs that reached a significant P-value within the study cohort and merely confirmed the frequency of already-established risk-carrying CNVs. As a result, CNVs with a very low frequency that might be relevant for SCZ susceptibility are lost for secondary analyses. In this study, we provide a concise collection of high-quality CNVs in a large German sample consisting of 1,637 patients with SCZ or schizoaffective disorder and 1,627 controls. All individuals were genotyped on Illumina''s BeadChips and putative CNVs were identified using QuantiSNP and PennCNV. Only those CNVs that were detected by both programs and spanned ≥30 consecutive SNPs were included in the data collection and downstream analyses (2,366 CNVs, 0.73 CNVs per individual). The genome-wide analysis did not reveal a specific association between a previously unknown CNV and SCZ. However, the group of CNVs previously reported to be associated with SCZ was more frequent in our patients than in the controls. The publication of our dataset will serve as a unique, easily accessible, high-quality CNV data collection for other research groups. The dataset could be useful for the identification of new disease-relevant CNVs that are currently overlooked due to their very low frequency and lack of power for their detection in individual studies.     

A Bioinformatician's Guide to Metagenomics

Summary: As random shotgun metagenomic projects proliferate and become the dominant source of publicly available sequence data, procedures for the best practices in their execution and analysis become increasingly important. Based on our experience at the Joint Genome Institute, we describe the chain of decisions accompanying a metagenomic project from the viewpoint of the bioinformatic analysis step by step. We guide the reader through a standard workflow for a metagenomic project beginning with presequencing considerations such as community composition and sequence data type that will greatly influence downstream analyses. We proceed with recommendations for sampling and data generation including sample and metadata collection, community profiling, construction of shotgun libraries, and sequencing strategies. We then discuss the application of generic sequence processing steps (read preprocessing, assembly, and gene prediction and annotation) to metagenomic data sets in contrast to genome projects. Different types of data analyses particular to metagenomes are then presented, including binning, dominant population analysis, and gene-centric analysis. Finally, data management issues are presented and discussed. We hope that this review will assist bioinformaticians and biologists in making better-informed decisions on their journey during a metagenomic project.     

From “Haus Tambaran” to Church: Continuity and Change in Contemporary Papua New Guinean Architecture

ABSTRACT

This article examines contemporary Papua New Guinean architecture created in the oscillation between Melanesian culture and Western impact. Some of the country's indigenous buildings are truly remarkable, especially the prestigious structures known as “Haus Tambaran” in the Sepik River area which have lent inspiration to many outstanding samples of contemporary Papua New Guinean design. We have studied both the indigenous and contemporary architecture of the Sepik region in the field and in additional research in collaboration with the late Professor Wallace Ruff and are comparing and contrasting contemporary architectural design with indigenous buildings. Here, we focus on a church at Ambunti, East Sepik Province. There is no electricity available on the site to facilitate climate control. Moreover, this contemporary building serves Western political, social, religious and educational functions. At the same time, the church incorporates aspects of the country's architectural heritage, including aesthetics as well as site-design and design with climate. Our comparison contrasts the modern building's functions, aesthetics, and design solutions with the area's indigenous local equivalent, the Haus Tambaran, and reveals elements borrowed, left aside, or altered in the process of adaptation. Issues discussed here include historic precedent, aesthetics, ownership, gender, and other social issues, as well as design and construction. Formal aspects, their meanings and functions, as well as environmental considerations and design solutions are borrowed, translated, or transformed, recalling but also differing from “Green Architecture,” to serve contemporary Western needs.     

SENSORY PROFILING WITH PROBABILISTIC MULTIDIMENSIONAL SCALING

Variability is a fundamental characteristic of sensory profile data. Ignoring the variability may result in biased solutions that cannot be improved by the collection of additional data. Probabilistic multidimensional scaling (PMDS) models provide a means of accounting for the variability inherent in sensory data by using distributions, instead of points, to portray sensory objects. For profile data with high levels of variability, the probabilistic model recovers latent structure parameters very well — traditional deterministic MDS models and principal components analyses (PCA) do not. Advantages of the PMDS models include their parsimony, testability and extensibility. Two particularly attractive PMDS attributes are their ability to relate consumers' expressions of liking to product profiles and their ability to estimate a product's " perceptual share" from liking and profile data. Used as a criterion with what-if modeling, perceptual share estimates enable the evaluation of alternative product development strategies.     

Toward supportive data collection tools for plant metabolomics

Over recent years, a number of initiatives have proposed standard reporting guidelines for functional genomics experiments. Associated with these are data models that may be used as the basis of the design of software tools that store and transmit experiment data in standard formats. Central to the success of such data handling tools is their usability. Successful data handling tools are expected to yield benefits in time saving and in quality assurance. Here, we describe the collection of datasets that conform to the recently proposed data model for plant metabolomics known as ArMet (architecture for metabolomics) and illustrate a number of approaches to robust data collection that have been developed in collaboration between software engineers and biologists. These examples also serve to validate ArMet from the data collection perspective by demonstrating that a range of software tools, supporting data recording and data upload to central databases, can be built using the data model as the basis of their design.     

Lake pigments facilitate analysis of fecal cortisol and behavior in group-housed macaques

Fecal steroid analyses are becoming more popular among both field and laboratory scientists. The benefits associated with sampling procedures that do not require restraint, anesthesia, and blood collection include less risk to both subject and investigator, as well as the potential to obtain endocrine profiles that do not reflect the influence of stress. However, the utility of the fecal steroid method has been limited in field conditions because of problems associated with sample identification. Here, we present evidence that Lake pigments are a valuable tool for the identification of individual fecal samples from group-housed female cynomolgus macaques. Further, we present data that suggest that excreted cortisol can be assayed from such samples, leading to the finding that time of day of sample collection influences cortisol concentrations, with morning samples producing higher values (t = 2.769, P = 0.024). Finally, the collection of physiological data from group-housed animals permits the evaluation of the relationship between endocrine status and behavior. This study demonstrated that morning fecal cortisol was significantly correlated with competitive and proximity behaviors, although not with rank in two stable social groups. In conclusion, the utility and validity of fecal steroid analyses continue to expand with further investigations.     

Methods of developing a core collection of annual Medicago species

A core collection is a subset of a large germplasm collection that contains accessions chosen to represent the genetic variability of the germplasm collection. The purpose of the core collection is to improve management and use of a germplasm collection. Core collections are usually assembled by grouping accessions and selecting from within these groups. The objective of this study was to compare 11 methods of assembling a core collection of the U.S. National collection of annual Medicago species. These methods differed in their use of passport and evaluation data as well as their selection strategy. Another objective was to compare core collections with sample sizes of 5%, 10% and 17% of the germplasm collection. Core collections assembled with evaluation data and cluster analysis better represented the germplasm collection than core collections assembled based solely on passport data and random selection of accessions, The Relative Diversity and the logarithm methods generated better core collections than the proportional method. The 5% and 10% sample size core collection were judged insufficient to represent the germplasm collection.     

Different hunting strategies select for different weights in red deer

Much insight can be derived from records of shot animals. Most researchers using such data assume that their data represents a random sample of a particular demographic class. However, hunters typically select a non-random subset of the population and hunting is, therefore, not a random process. Here, with red deer (Cervus elaphus) hunting data from a ranch in Toledo, Spain, we demonstrate that data collection methods have a significant influence upon the apparent relationship between age and weight. We argue that a failure to correct for such methodological bias may have significant consequences for the interpretation of analyses involving weight or correlated traits such as breeding success, and urge researchers to explore methods to identify and correct for such bias in their data.     

Data Quality and the Comparative Method: The Case of Primate Group Size

The comparative method is frequently employed to study primate behavior and evolution. The method is used to infer adaptations, and considerable improvements have been made with respect to its implementation. Despite these advances, scant attention has been given to the nature of the data that are used in comparative analyses. This creates a potential problem as data are often compiled from studies conducted by multiple researchers, whose methods may differ, resulting in variation in data quality. In this article, we investigate the quality of data employed in studies of primate group size. Several issues concerning data quality arise when assembling data on group size. For example, data quality may be compromised if group sizes are estimated from censuses, unhabituated groups, or groups with unrecognized individuals. To mitigate these and other data quality issues, we gathered data from the literature on 23 monkeys and apes using well-defined and biologically relevant criteria for inclusion. We compare our results with those of eight published compilations of group size. Most studies did not provide details regarding the criteria for including data. We found that our group size values were uncorrelated or weakly correlated with those from three other studies and differed in a consistent fashion from those of one other study. Because conclusions derived from comparative analyses are only as accurate as the data that they use, future studies should provide details regarding data collection to ensure their reliability.     

Smoothness selection for penalized quantile regression splines

Modern data-rich analyses may call for fitting a large number of nonparametric quantile regressions. For example, growth charts may be constructed for each of a collection of variables, to identify those for which individuals with a disorder tend to fall in the tails of their age-specific distribution; such variables might serve as developmental biomarkers. When such a large set of analyses are carried out by penalized spline smoothing, reliable automatic selection of the smoothing parameter is particularly important. We show that two popular methods for smoothness selection may tend to overfit when estimating extreme quantiles as a smooth function of a predictor such as age; and that improved results can be obtained by multifold cross-validation or by a novel likelihood approach. A simulation study, and an application to a functional magnetic resonance imaging data set, demonstrate the favorable performance of our methods.     

Enhancing repository fungal data for biogeographic analyses

Open-access occurrence data are useful for studying spatial patterns of fungi, but often have quality issues. These include errors in taxonomy and geo-coordinates, and incomplete coverage across areas and taxonomic groups. We identify 15 quality issues that can lead to incorrect biogeographic inference, and develop a reproducible pipeline that flags and removes problematic entries. This pipeline tests accuracy of geographic records and names. Then, if information on non-native status is unavailable or unreliable, it detects non-native species via a predictive model. Finally, it identifies spatial and environmental outliers and removes them when biologically improbable. We test the pipeline by cleaning data for Australian fungi, with 251,642 records retained after cleaning the initial 1,034,601 records. Exploratory analysis showed that the cleaned data is useful for analyses such as biogeographic regionalisation, but recording gaps and lack of saturation in collection effort also caution that more surveys are needed to improve collection completeness.     

A critique of comparative studies of brain size

In recent years, there have been over 50 comparative analyses carried out in which social or ecological variables have been used to explain variation in whole brain size, or a part thereof, in a range of vertebrate species. Here, we review this body of work, pointing out that there are a number of substantial problems with some of the assumptions that underpin the hypotheses (e.g. what brain size means), with the data collection and with the ways in which the data are combined in the analyses. These problems are particularly apparent in those analyses in which attempts are made to correlate complex behaviour with parts of the brain that carry out multiple functions. We conclude that now is the time to substantiate these results with data from experimental manipulations.     

Energetic modelling: A comparison of the different approaches used in seabirds

Studying energetics of marine top predators is essential to understand their role within food-webs and mechanisms associated with their survival and population dynamics. Several methods exist to estimate energy expenditure in captive and free-ranging animals. However, most of them are difficult to implement, restrained to specific periods, and are consequently inappropriate for seabirds. Supplementary and complementary approaches are therefore needed, and the use of modelling appears as an excellent option allowing energetic studies when field data collection is challenging. Currently three main energetics models are used, with various degrees of complexity and accuracy: allometric equations, time–energy-budget analyses and thermodynamic models. However, a comparison of their practicability and accuracy was still lacking. Here, we present an overview of these 3 model types, their characteristics, advantages and disadvantages, and areas of application in seabirds. We then investigate their accuracy by using them in parallel for the same dataset, and by comparing outputs with direct measurements (doubly-labelled water technique). We show that, when detailed data are available, time–energy–budget analysis is the best model to accurately predict seabird energy expenditures. Conversely, thermodynamic modelling allows reasonably accurate calculations when field data are scarce, and is therefore ideal to study energetics during the inter-breeding season.     

MolMovDB: analysis and visualization of conformational change and structural flexibility

The Database of Macromolecular Movements (http://MolMovDB.org) is a collection of data and software pertaining to flexibility in protein and RNA structures. The database is organized into two parts. Firstly, a collection of 'morphs' of solved structures representing different states of a molecule provides quantitative data for flexibility and a number of graphical representations. Secondly, a classification of known motions according to type of conformational change (e.g. 'hinged domain' or 'allosteric') incorporates textual annotation and information from the literature relating to the motion, linking together many of the morphs. A variety of subsets of the morphs are being developed for use in statistical analyses. In particular, for each subset it is possible to derive distributions of various motional quantities (e.g. maximum rotation) that can be used to place a specific motion in context as being typical or atypical for a given population. Over the past year, the database has been greatly expanded and enhanced to incorporate new structures and to improve the quality of data. The 'morph server', which enables users of the database to add new morphs either from their own research or the PDB, has also been enhanced to handle nucleic acid structures and multi-chain complexes.     

The use of electronic monitoring within tuna longline fisheries: implications for international data collection,analysis and reporting

Electronic monitoring (EM) consisting of on-board video imagery and on-shore analysis, offers an alternative or supplement to at-sea observer programs in commercial fisheries. In the western and central Pacific Ocean (WCPO), where observer coverage in most tuna longline fisheries has historically been?<?5%, the advent of EM has been perceived as a tool for meeting international data collection and exchange obligations. However, the capability of EM to collect and support interpretation of records into data for all fields currently collected by at-sea observers is still under assessment. We use the Western and Central Pacific Fisheries Commission (WCPFC) as a case-study to evaluate the longline WCPFC regional observer programme minimum standard data fields, their current scientific application, the proportion of member countries exchanging data and the capability of EM technology to collect these fields. We identify that 78% of the longline fields can be collected with current EM technology, with 84% of these used in scientific analyses. For the 16% of fields not routinely used in scientific analyses, the introduction of EM may facilitate a sufficient increase in data availability to support their future use. Alternative tools would be required to collect fields that EM could not record to ensure data continuity and scientific rigour are not compromised. In examining the capability of EM in the context of WCPFC member state requirements under international law, we advocate for a holistic and integrated approach to the use of EM in future research and monitoring programs in both the WCPO and global longline fisheries.     

Prospects for elucidating the phylogeny of the Apicomplexa

The Apicomplexa is traditionally considered to contain four clearly defined groups, but the phylogenetic relationships among these groups, and their subsequent taxonomic arrangement, are currently unclear. Here, I consider five of the important criteria that need to be met before radical taxonomic changes are made, in relation to phylogenetic analyses. Unfortunately, at least four of these criteria indicate that the prospects for elucidating the phylogeny and taxonomy of the Apicomplexa are not good in the short term. A lot more pertinent data need to be collected, both in terms of taxa sampled and genes sequenced, before any concordance among phylogenies is likely to emerge; and someone (e.g. a consortium) needs to coordinate the active collection and analysis of these data if any worthwhile progress is to be made.     

Review of Information Resources to Support Human Exposure Assessment Models

Efforts to model human exposures to chemicals are growing more sophisticated and encompass increasingly complex exposure scenarios. The scope of such analyses has increased, growing from assessments of single exposure pathways to complex evaluations of aggregate or cumulative chemical exposures occurring within a variety of settings and scenarios. In addition, quantitative modeling techniques have evolved from simple deterministic analyses using single point estimates for each necessary input parameter to more detailed probabilistic analyses that can accommodate distributions of input parameters and assessment results. As part of an overall effort to guide development of a comprehensive framework for modeling human exposures to chemicals, available information resources needed to derive input parameters for human exposure assessment models were compiled and critically reviewed. Ongoing research in the area of exposure assessment parameters was also identified. The results of these efforts are summarized and other relevant information that will be needed to apply the available data in a comprehensive exposure model is discussed. Critical data gaps in the available information are also identified. Exposure assessment modeling and associated research would benefit from the collection of additional data as well as by enhancing the accessibility of existing and evolving information resources.     

Reassessment of the Microbial Role in Mn-Fe Nodule Genesis in Andean Paleosols

The presence of Mn-Fe nodules in the epipedons (surface horizons) of paleosols of presumed Upper Neogene age in the northwestern Venezuelan Andes have been interpreted as products of inorganic oxidation and reduction processes operating over the full range of glacial and interglacial cycles that affected paleosol morphogenesis. New microscopic/chemical data from combined SEM-EDS-FIB analyses of representative Mn-Fe nodules indicate microbes play an important role in Mn/Fe precipitation leading to their genesis in alpine Mollisols (Argiustolls). Although the prevailing new data are based mainly on fossil forms of filamentous bacteria and fungi and other biogenic pseudomorphs that may represent the former resident bacteria, the presence of extant microbes must await field experiments/collection, followed by a molecular microbiology approach to determine the biological drivers of metal precipitation. As in other terrestrial niche environments, microbes are seen here to play a role, perhaps a key one, in the morphogenesis of paleosols of importance in upper Neogene paleoenvironmental reconstruction.     

Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation

In the present work, we demonstrate a method for concurrent collection of EEG/fMRI data. In our setup, EEG data are collected using a high-density 256-channel sensor net. The EEG amplifier itself is contained in a field isolation containment system (FICS), and MRI clock signals are synchronized with EEG data collection for subsequent MR artifact characterization and removal. We demonstrate this method first for resting state data collection. Thereafter, we demonstrate a protocol for EEG/fMRI data recording, while subjects listen to a tape asking them to visualize that their left hand is immersed in a cold-water bath and referred to, here, as the cold glove paradigm. Thermal differentials between each hand are measured throughout EEG/fMRI data collection using an MR compatible temperature sensor that we developed for this purpose. We collect cold glove EEG/fMRI data along with simultaneous differential hand temperature measurements both before and after hypnotic induction. Between pre and post sessions, single modality EEG data are collected during the hypnotic induction and depth assessment process. Our representative results demonstrate that significant changes in the EEG power spectrum can be measured during hypnotic induction, and that hand temperature changes during the cold glove paradigm can be detected rapidly using our MR compatible differential thermometry device.