The Expected Behaviors of Posterior Predictive Tests and Their Unexpected Interpretation.

Poor fit between models of sequence or trait evolution and empirical data is known to cause biases and lead to spurious conclusions about evolutionary patterns and processes. Bayesian posterior prediction is a flexible and intuitive approach for detecting such cases of poor fit. However, the expected behavior of posterior predictive tests has never been characterized for evolutionary models, which is critical for their proper interpretation. Here, we show that the expected distribution of posterior predictive P-values is generally not uniform, in contrast to frequentist P-values used for hypothesis testing, and extreme posterior predictive P-values often provide more evidence of poor fit than typically appreciated. Posterior prediction assesses model adequacy under highly favorable circumstances, because the model is fitted to the data, which leads to expected distributions that are often concentrated around intermediate values. Nonuniform expected distributions of P-values do not pose a problem for the application of these tests, however, and posterior predictive P-values can be interpreted as the posterior probability that the fitted model would predict a dataset with a test statistic value as extreme as the value calculated from the observed data.

On the Need for New Measures of Phylogenomic Support.

The scale of data sets used to infer phylogenies has grown dramatically in the last decades, providing researchers with an enormous amount of information with which to draw inferences about evolutionary history. However, standard approaches to assessing confidence in those inferences (e.g., nonparametric bootstrap proportions [BP] and Bayesian posterior probabilities [PPs]) are still deeply influenced by statistical procedures and frameworks that were developed when information was much more limited. These approaches largely quantify uncertainty caused by limited amounts of data, which is often vanishingly small with modern, genome-scale sequence data sets. As a consequence, today's phylogenomic studies routinely report near-complete confidence in their inferences, even when different studies reach strongly conflicting conclusions and the sites and loci in a single data set contain much more heterogeneity than our methods assume or can accommodate. Therefore, we argue that BPs and marginal PPs of bipartitions have outlived their utility as the primary means of measuring phylogenetic support for modern phylogenomic data sets with large numbers of sites relative to the number of taxa. Continuing to rely on these measures will hinder progress towards understanding remaining sources of uncertainty in the most challenging portions of the Tree of Life. Instead, we encourage researchers to examine the ideas and methods presented in this special issue of Systematic Biology and to explore the area further in their own work. The papers in this special issue outline strategies for assessing confidence and uncertainty in phylogenomic data sets that move beyond stochastic error due to limited data and offer promise for more productive dialogue about the challenges that we face in reaching our shared goal of understanding the history of life on Earth.[Big data; gene tree variation; genomic era; statistical bias.].

Comparing Likelihood Ratios to Understand Genome-Wide Variation in Phylogenetic Support.

Genomic data have only sometimes brought resolution to the tree of life. Large phylogenomic studies can reach conflicting conclusions about important relationships, with mutually exclusive hypotheses receiving strong support. Reconciling such differences requires a detailed understanding of how phylogenetic signal varies among data sets. Two complementary strategies for better understanding phylogenomic conflicts are to examine support on a locus-by-locus basis and use support values that capture a larger range of variation in phylogenetic information, such as likelihood ratios. Likelihood ratios can be calculated using either maximum or marginal likelihoods. Despite being conceptually similar, differences in how these ratios are calculated and interpreted have not been closely examined in phylogenomics. Here, we compare the behavior of maximum and marginal likelihood ratios when evaluating alternate resolutions of recalcitrant relationships among major squamate lineages. We find that these ratios are broadly correlated between loci, but the correlation is driven by extreme values. As a consequence, the proportion of loci that support a hypothesis can change depending on which ratio is used and whether smaller values are discarded. In addition, maximum likelihood ratios frequently exhibit identical support for alternate hypotheses, making conflict resolution a challenge. We find surprising support for a sister relationship between snakes and iguanians across four different phylogenomic data sets in contrast to previous empirical studies. [Bayes factors; likelihood ratios; marginal likelihood; maximum likelihood; phylogenomics; squamates.].

Reflective, pragmatic, and reactive decision-making by maternity service providers during the SARS-CoV-2 pandemic health system shock: a qualitative, grounded theory analysis.

BACKGROUND: Pregnant and postpartum women were identified as having particular vulnerability to severe symptomatology of SARS-CoV-2 infection, so maternity services significantly reconfigured their care provision. We examined the experiences and perceptions of maternity care staff who provided care during the pandemic in South London, United Kingdom - a region of high ethnic diversity with varied levels of social complexity. METHODS: We conducted a qualitative interview study, as part of a service evaluation between August and November 2020, using in-depth, semi-structured interviews with a range of staff (N = 29) working in maternity services. Data were analysed using Grounded Theory analysis appropriate to cross-disciplinary health research. ANALYSIS & FINDINGS: Maternity healthcare professionals provided their views, experiences, and perceptions of delivering care during the pandemic. Analysis rendered three emergent themes regarding decision-making during reconfigured maternity service provision, organised into pathways: 1) 'Reflective decision-making'; 2) 'Pragmatic decision-making'; and 3) 'Reactive decision-making'. Whilst pragmatic decision-making was found to disrupt care, reactive-decision-making was perceived to devalue the care offered and provided. Alternatively, reflective decision-making, despite the difficult working conditions of the pandemic, was seen to benefit services, with regards to care of high-quality, sustainability of staff, and innovation within the service. CONCLUSIONS: Decision-making within maternity care was found to take three forms - where at best changes to services could be innovative, at worst they could cause devaluation in care being delivered, and more often than not, these changes were disruptive. With regard to positive changes, healthcare providers identified staff empowerment, flexible working patterns (both for themselves and collectively as teams), personalised care delivery, and change-making in general, as key areas to capitalise on current and ongoing innovations borne out of the pandemic. Key learnings included a focus on care-related, meaningful listening and engagement of staff at all levels, in order to drive forward high-quality care and avoid care disruption and devaluation.

Phylogenomics Reveals Ancient Gene Tree Discordance in the Amphibian Tree of Life.

Molecular phylogenies have yielded strong support for many parts of the amphibian Tree of Life, but poor support for the resolution of deeper nodes, including relationships among families and orders. To clarify these relationships, we provide a phylogenomic perspective on amphibian relationships by developing a taxon-specific Anchored Hybrid Enrichment protocol targeting hundreds of conserved exons which are effective across the class. After obtaining data from 220 loci for 286 species (representing 94% of the families and 44% of the genera), we estimate a phylogeny for extant amphibians and identify gene tree-species tree conflict across the deepest branches of the amphibian phylogeny. We perform locus-by-locus genealogical interrogation of alternative topological hypotheses for amphibian monophyly, focusing on interordinal relationships. We find that phylogenetic signal deep in the amphibian phylogeny varies greatly across loci in a manner that is consistent with incomplete lineage sorting in the ancestral lineage of extant amphibians. Our results overwhelmingly support amphibian monophyly and a sister relationship between frogs and salamanders, consistent with the Batrachia hypothesis. Species tree analyses converge on a small set of topological hypotheses for the relationships among extant amphibian families. These results clarify several contentious portions of the amphibian Tree of Life, which in conjunction with a set of vetted fossil calibrations, support a surprisingly younger timescale for crown and ordinal amphibian diversification than previously reported. More broadly, our study provides insight into the sources, magnitudes, and heterogeneity of support across loci in phylogenomic data sets.[AIC; Amphibia; Batrachia; Phylogeny; gene tree-species tree discordance; genomics; information theory.].

Six generations of CHMP2B-mediated Frontotemporal Dementia: Clinical features, predictive testing, progression, and survival.

OBJECTIVES: Chromosome 3-linked frontotemporal dementia (FTD-3) is caused by a c.532-1G > C mutation in the CHMP2B gene. It is extensively studied in a Danish family comprising one of the largest families with an autosomal dominantly inherited frontotemporal dementia (FTD). This retrospective cohort study utilizes demographics to identify risk factors for onset, progression, life expectancy, and death in CHMP2B-mediated FTD. The pedigree of 528 individuals in six generations is provided, and clinical descriptions are presented. Choices of genetic testing are evaluated. MATERIALS AND METHODS: Demographic and lifestyle factors were assessed in survival analysis in all identified CHMP2B mutation carriers (44 clinically affected FTD-3 patients and 16 presymptomatic CHMP2B mutation carriers). Predictors of onset and progression included sex, parental disease course, education, and vascular risk factors. Life expectancy was established by matching CHMP2B mutation carriers with average life expectancies in Denmark. RESULTS: Disease course was not correlated to parental disease course and seemed unmodified by lifestyle factors. Diagnosis was recognized at an earlier age in members with higher levels of education, probably reflecting an early dysexecutive syndrome, unmasked earlier in people with higher work-related requirements. Carriers of the CHMP2B mutation had a significant reduction in life expectancy of 13 years. Predictive genetic testing was chosen by 20% of at-risk family members. CONCLUSIONS: CHMP2B-mediated FTD is substantiated as an autosomal dominantly inherited disease of complete penetrance. The clinical phenotype is a behavioral variant FTD. The disease course is unpredictable, and life expectancy is reduced. The findings may be applicable to other genetic FTD subtypes.

Precarity and preparedness during the SARS-CoV-2 pandemic: A qualitative service evaluation of maternity healthcare professionals.

INTRODUCTION: The SARS-CoV-2 pandemic has devastated populations, posing unprecedented challenges for healthcare services, staff and service-users. In the UK, rapid reconfiguration of maternity healthcare service provision changed the landscape of antenatal, intrapartum and postnatal care. This study aimed to explore the experiences of maternity services staff who provided maternity care during the SARS-CoV-2 pandemic to inform future improvements in care. MATERIAL AND METHODS: A qualitative interview service evaluation was undertaken at a single maternity service in an NHS Trust, South London. Respondents (n = 29) were recruited using a critical case purposeful sample of maternity services staff. Interviews were conducted using video-conferencing software, and were transcribed and analyzed using Grounded Theory Analysis appropriate for cross-disciplinary health research. The focus of analysis was on staff experiences of delivering maternity services and care during the SARS-CoV-2 pandemic. RESULTS: A theory of "Precarity and Preparedness" was developed, comprising three main emergent themes: "Endemic precarity: A health system under pressure"; "A top-down approach to managing the health system shock"; and "From un(der)-prepared to future flourishing". CONCLUSIONS: Maternity services in the UK were under significant strain and were inherently precarious. This was exacerbated by the SARS-CoV-2 pandemic, which saw further disruption to service provision, fragmentation of care and pre-existing staff shortages. Positive changes are required to improve staff retention and team cohesion, and ensure patient-centered care remains at the heart of maternity care.

P3: Phylogenetic Posterior Prediction in RevBayes.

Tests of absolute model fit are crucial in model-based inference because poorly structured models can lead to biased parameter estimates. In Bayesian inference, posterior predictive simulations can be used to test absolute model fit. However, such tests have not been commonly practiced in phylogenetic inference due to a lack of convenient and flexible software. Here, we describe our newly implemented tests of model fit using posterior predictive testing, based on both data- and inference-based test statistics, in the phylogenetics software RevBayes. This new implementation makes a large spectrum of models available for use through a user-friendly and flexible interface.

The Behavior of Metropolis-Coupled Markov Chains When Sampling Rugged Phylogenetic Distributions.

Bayesian phylogenetic inference relies on the use of Markov chain Monte Carlo (MCMC) to provide numerical approximations of high-dimensional integrals and estimate posterior probabilities. However, MCMC performs poorly when posteriors are very rugged (i.e., regions of high posterior density are separated by regions of low posterior density). One technique that has become popular for improving numerical estimates from MCMC when distributions are rugged is Metropolis coupling (MC$^3$). In MC$^3$, additional chains are employed to sample flattened transformations of the posterior and improve mixing. Here, we highlight several underappreciated behaviors of MC3. Notably, estimated posterior probabilities may be incorrect but appear to converge, when individual chains do not mix well, despite different chains sampling trees from all relevant areas in tree space. Counterintuitively, such behavior can be more difficult to diagnose with increased numbers of chains. We illustrate these surprising behaviors of MC$^3$ using a simple, non-phylogenetic example and phylogenetic examples involving both constrained and unconstrained analyses. To detect and mitigate the effects of these behaviors, we recommend increasing the number of independent analyses and varying the temperature of the hottest chain in current versions of Bayesian phylogenetic software. Convergence diagnostics based on the behavior of the hottest chain may also help detect these behaviors and could form a useful addition to future software releases.

Impact of Model Violations on the Inference of Species Boundaries Under the Multispecies Coalescent.

The use of genetic data for identifying species-level lineages across the tree of life has received increasing attention in the field of systematics over the past decade. The multispecies coalescent model provides a framework for understanding the process of lineage divergence and has become widely adopted for delimiting species. However, because these studies lack an explicit assessment of model fit, in many cases, the accuracy of the inferred species boundaries are unknown. This is concerning given the large amount of empirical data and theory that highlight the complexity of the speciation process. Here, we seek to fill this gap by using simulation to characterize the sensitivity of inference under the multispecies coalescent (MSC) to several violations of model assumptions thought to be common in empirical data. We also assess the fit of the MSC model to empirical data in the context of species delimitation. Our results show substantial variation in model fit across data sets. Posterior predictive tests find the poorest model performance in data sets that were hypothesized to be impacted by model violations. We also show that while the inferences assuming the MSC are robust to minor model violations, such inferences can be biased under some biologically plausible scenarios. Taken together, these results suggest that researchers can identify individual data sets in which species delimitation under the MSC is likely to be problematic, thereby highlighting the cases where additional lines of evidence to identify species boundaries are particularly important to collect. Our study supports a growing body of work highlighting the importance of model checking in phylogenetics, and the usefulness of tailoring tests of model fit to assess the reliability of particular inferences. [Populations structure, gene flow, demographic changes, posterior prediction, simulation, genetics.].

Variation Across Mitochondrial Gene Trees Provides Evidence for Systematic Error: How Much Gene Tree Variation Is Biological?

The use of large genomic data sets in phylogenetics has highlighted extensive topological variation across genes. Much of this discordance is assumed to result from biological processes. However, variation among gene trees can also be a consequence of systematic error driven by poor model fit, and the relative importance of biological vs. methodological factors in explaining gene tree variation is a major unresolved question. Using mitochondrial genomes to control for biological causes of gene tree variation, we estimate the extent of gene tree discordance driven by systematic error and employ posterior prediction to highlight the role of model fit in producing this discordance. We find that the amount of discordance among mitochondrial gene trees is similar to the amount of discordance found in other studies that assume only biological causes of variation. This similarity suggests that the role of systematic error in generating gene tree variation is underappreciated and critical evaluation of fit between assumed models and the data used for inference is important for the resolution of unresolved phylogenetic questions.

Multi-disciplinary training hubs in North West England: the training hub lead perspective.

Introduction: Increasing the capacity of Primary Care to meet the challenge of providing future complex and multi-disciplinary care in England has led to the increasing establishment of 'Training Hubs' [TH]. Other terms are used interchangeably to refer to TH activity: Advanced Training Practices, Enhanced Training Practices and Community Education Providers. The aim of this study was to gather the perceptions of TH Leads in North West England on how they established their TH and lessons learned. Methods: Five semi-structured telephone interviews were undertaken with TH Leads. Thematic analysis of the transcripts was undertaken. Findings: Four themes were identified: Motivation and Expectations of Establishing THs; Benefits to Learners and Practice Staff; Implementation Challenges and Barriers to Scale-Up; Sustainability and Wider Implementation. Discussion: TH Leads highlighted that the establishment of THs enhanced the multi-disciplinary learning experience. However, several barriers for sustaining the quality of the TH learning environments were identified. Difficulties recruiting 'Spoke Practices' were greater than expected. Findings identified the following factors for consideration for wider implementation: the maintenance of TH Lead support networks; appropriateness of funding to encourage practices who may be reluctant to take on this additional responsibility; the importance of communication channels between THs and HEIs; careful management of students numbers.

Bayes Factors Unmask Highly Variable Information Content, Bias, and Extreme Influence in Phylogenomic Analyses.

As the application of genomic data in phylogenetics has become routine, a number of cases have arisen where alternative data sets strongly support conflicting conclusions. This sensitivity to analytical decisions has prevented firm resolution of some of the most recalcitrant nodes in the tree of life. To better understand the causes and nature of this sensitivity, we analyzed several phylogenomic data sets using an alternative measure of topological support (the Bayes factor) that both demonstrates and averts several limitations of more frequently employed support measures (such as Markov chain Monte Carlo estimates of posterior probabilities). Bayes factors reveal important, previously hidden, differences across six "phylogenomic" data sets collected to resolve the phylogenetic placement of turtles within Amniota. These data sets vary substantially in their support for well-established amniote relationships, particularly in the proportion of genes that contain extreme amounts of information as well as the proportion that strongly reject these uncontroversial relationships. All six data sets contain little information to resolve the phylogenetic placement of turtles relative to other amniotes. Bayes factors also reveal that a very small number of extremely influential genes (less than 1% of genes in a data set) can fundamentally change significant phylogenetic conclusions. In one example, these genes are shown to contain previously unrecognized paralogs. This study demonstrates both that the resolution of difficult phylogenomic problems remains sensitive to seemingly minor analysis details and that Bayes factors are a valuable tool for identifying and solving these challenges.

TreeScaper: Visualizing and Extracting Phylogenetic Signal from Sets of Trees.

Modern phylogenomic analyses often result in large collections of phylogenetic trees representing uncertainty in individual gene trees, variation across genes, or both. Extracting phylogenetic signal from these tree sets can be challenging, as they are difficult to visualize, explore, and quantify. To overcome some of these challenges, we have developed TreeScaper, an application for tree set visualization as well as the identification of distinct phylogenetic signals. GUI and command-line versions of TreeScaper and a manual with tutorials can be downloaded from https://github.com/whuang08/TreeScaper/releases TreeScaper is distributed under the GNU General Public License.

The Test Your Memory for Mild Cognitive Impairment (TYM-MCI).

BACKGROUND: To validate a short cognitive test: the Test Your Memory for Mild Cognitive Impairment (TYM-MCI) in the diagnosis of patients with amnestic mild cognitive impairment or mild Alzheimer's disease (aMCI/AD). METHODS: Two hundred and two patients with mild memory problems were recruited. All had 'passed' the Mini-Mental State Examination (MMSE). Patients completed the TYM-MCI, the Test Your Memory test (TYM), MMSE and revised Addenbrooke's Cognitive Examination (ACE-R), had a neurological examination, clinical diagnostics and multidisciplinary team review. RESULTS: As a single test, the TYM-MCI performed as well as the ACE-R in the distinction of patients with aMCI/AD from patients with subjective memory impairment with a sensitivity of 0.79 and specificity of 0.91. Used in combination with the ACE-R, it provided additional value and identified almost all cases of aMCI/AD. The TYM-MCI correctly classified most patients who had equivocal ACE-R scores. Integrated discriminant improvement analysis showed that the TYM-MCI added value to the conventional memory assessment. Patients initially diagnosed as unknown or with subjective memory impairment who were later rediagnosed with aMCI/AD scored poorly on their original TYM-MCI. CONCLUSION: The TYM-MCI is a powerful short cognitive test that examines verbal and visual recall and is a valuable addition to the assessment of patients with aMCI/AD. It is simple and cheap to administer and requires minimal staff time and training.

An evaluation of National Health Service England's Care Maker Programme: A mixed-methods analysis.

AIMS AND OBJECTIVES: To investigate the impact and sustainability of the Care Maker programme across England from the perspective of those involved in its delivery. BACKGROUND: The Care Maker programme was launched in England in 2013. It aims to support the "Compassion in Practice" strategy, with particular emphasis on the 6Cs of care, compassion, competence, communication, courage and commitment. Care Makers were recruited in an ambassadorial role. The intention was to inspire individuals throughout the National Health Service in England to bridge national policy with those delivering care. DESIGN: A mixed methods design was chosen, but this article focuses on two of the four distinct empirical data collection phases undertaken as part of this evaluation: a questionnaire with Care Makers; and two case studies of separate National Health Service trust sites. METHOD: Data were collected for this evaluation in 2015. An online questionnaire was distributed to the total population of Care Makers across the National Health Service in England. It included a combination of open and closed questions. The case studies involved semistructured telephone interviews with a range of professionals engaged with the Care Maker programme across the trust sites. RESULTS: Care Makers reported that participation in the programme had offered opportunities in terms of improving the quality-of-care provision in the workplace as well as contributing towards their own professional development. CONCLUSION: The Care Maker programme has supported and helped underpin the nursing, midwifery and care strategy "Compassion in Practice". RELEVANCE TO CLINICAL PRACTICE: This model of using volunteers to embed strategy and policy could potentially be used in other areas of clinical practice and indeed in other countries.

EmpPrior: using outside empirical data to inform branch-length priors for Bayesian phylogenetics.

BACKGROUND: Branch-length parameters are a central component of phylogenetic models and of intrinsic biological interest. Default branch-length priors in some Bayesian phylogenetic software can be unintentionally informative and lead to branch- and tree-length estimates that are unreasonable. Alternatively, priors may be uninformative, but lead to diffuse posterior estimates. Despite the widespread availability of relevant datasets from other groups, biologists rarely leverage outside information to specify branch-length priors that are specific to the analysis they are conducting. RESULTS: We developed the software package EmpPrior to facilitate the collection and incorporation of relevant, outside information when setting branch-length priors for phylogenetics. EmpPrior efficiently queries TreeBASE to find data that are similar to focal data, in terms of taxonomic and genetic sampling, and uses them to inform branch-length priors for the focal analysis. EmpPrior consists of two components: EmpPrior-search, written in Java to query TreeBASE, and EmpPrior-fit, written in R to parameterize branch-length distributions. In an example analysis, we show how the use of relevant, outside data is made possible by EmpPrior and improves tree-length estimates from a focal dataset. CONCLUSION: EmpPrior is easy to use, fast, and improves both the accuracy and precision of branch-length estimates in many circumstances. While EmpPrior's focus is on branch lengths, the strategy it employs could easily be extended to address other prior parameterization problems in phylogenetics.

Deflating trees: improving Bayesian branch-length estimates using informed priors.

Prior distributions can have a strong effect on the results of Bayesian analyses. However, no general consensus exists for how priors should be set in all circumstances. Branch-length priors are of particular interest for phylogenetics, because they affect many parameters and biologically relevant inferences have been shown to be sensitive to the chosen prior distribution. Here, we explore the use of outside information to set informed branch-length priors and compare inferences from these informed analyses to those using default settings. For both the commonly used exponential and the newly proposed compound Dirichlet prior distributions, the incorporation of relevant outside information improves inferences for data sets that have produced problematic branch- and tree-length estimates under default settings. We suggest that informed priors are worthy of further exploration for phylogenetics.

Can We Identify Genes with Increased Phylogenetic Reliability?

Topological heterogeneity among gene trees is widely observed in phylogenomic analyses and some of this variation is likely caused by systematic error in gene tree estimation. Systematic error can be mitigated by improving models of sequence evolution to account for all evolutionary processes relevant to each gene or identifying those genes whose evolution best conforms to existing models. However, the best method for identifying such genes is not well established. Here, we ask if filtering genes according to their clock-likeness or posterior predictive effect size (PPES, an inference-based measure of model violation) improves phylogenetic reliability and congruence. We compared these approaches to each other, and to the common practice of filtering based on rate of evolution, using two different metrics. First, we compared gene-tree topologies to accepted reference topologies. Second, we examined topological similarity among gene trees in filtered sets. Our results suggest that filtering genes based on clock-likeness and PPES can yield a collection of genes with more reliable phylogenetic signal. For the two exemplar data sets we explored, from yeast and amniotes, clock-likeness and PPES outperformed rate-based filtering in both congruence and reliability.

A feasibility study of X-ray phase-contrast mammographic tomography at the Imaging and Medical beamline of the Australian Synchrotron.

Results are presented of a recent experiment at the Imaging and Medical beamline of the Australian Synchrotron intended to contribute to the implementation of low-dose high-sensitivity three-dimensional mammographic phase-contrast imaging, initially at synchrotrons and subsequently in hospitals and medical imaging clinics. The effect of such imaging parameters as X-ray energy, source size, detector resolution, sample-to-detector distance, scanning and data processing strategies in the case of propagation-based phase-contrast computed tomography (CT) have been tested, quantified, evaluated and optimized using a plastic phantom simulating relevant breast-tissue characteristics. Analysis of the data collected using a Hamamatsu CMOS Flat Panel Sensor, with a pixel size of 100 µm, revealed the presence of propagation-based phase contrast and demonstrated significant improvement of the quality of phase-contrast CT imaging compared with conventional (absorption-based) CT, at medically acceptable radiation doses.