motifDiverge: a model for assessing the statistical significance of gene regulatory motif divergence between two DNA sequences

Next-generation sequencing technology enables the identification of thousands of gene regulatory sequences in many cell types and organisms. We consider the problem of testing if two such sequences differ in their number of binding site motifs for a given transcription factor (TF) protein. Binding site motifs impart regulatory function by providing TFs the opportunity to bind to genomic elements and thereby affect the expression of nearby genes. Evolutionary changes to such functional DNA are hypothesized to be major contributors to phenotypic diversity within and between species; but despite the importance of TF motifs for gene expression, no method exists to test for motif loss or gain. Assuming that motif counts are Binomially distributed, and allowing for dependencies between motif instances in evolutionarily related sequences, we derive the probability mass function of the difference in motif counts between two nucleotide sequences. We provide a method to numerically estimate this distribution from genomic data and show through simulations that our estimator is accurate. Finally, we introduce the R package {\tt motifDiverge} that implements our methodology and illustrate its application to gene regulatory enhancers identified by a mouse developmental time course experiment. While this study was motivated by analysis of regulatory motifs, our results can be applied to any problem involving two correlated Bernoulli trials

Now the wars are over: The past, present and future of Scottish battlefields

Battlefield archaeology has provided a new way of appreciating historic battlefields. This paper provides a summary of the long history of warfare and conflict in Scotland which has given rise to a large number of battlefield sites. Recent moves to highlight the archaeological importance of these sites, in the form of Historic Scotland’s Battlefields Inventory are discussed, along with some of the problems associated with the preservation and management of these important cultural sites

Kinematic Motion Retargeting for Contact-Rich Anthropomorphic Manipulations

Hand motion capture data is now relatively easy to obtain, even for complicated grasps; however this data is of limited use without the ability to retarget it onto the hands of a specific character or robot. The target hand may differ dramatically in geometry, number of degrees of freedom (DOFs), or number of fingers. We present a simple, but effective framework capable of kinematically retargeting multiple human hand-object manipulations from a publicly available dataset to a wide assortment of kinematically and morphologically diverse target hands through the exploitation of contact areas. We do so by formulating the retarget operation as a non-isometric shape matching problem and use a combination of both surface contact and marker data to progressively estimate, refine, and fit the final target hand trajectory using inverse kinematics (IK). Foundational to our framework is the introduction of a novel shape matching process, which we show enables predictable and robust transfer of contact data over full manipulations while providing an intuitive means for artists to specify correspondences with relatively few inputs. We validate our framework through thirty demonstrations across five different hand shapes and six motions of different objects. We additionally compare our method against existing hand retargeting approaches. Finally, we demonstrate our method enabling novel capabilities such as object substitution and the ability to visualize the impact of design choices over full trajectories

Baby-Step Giant-Step Algorithms for the Symmetric Group

We study discrete logarithms in the setting of group actions. Suppose that $G$ is a group that acts on a set $S$. When $r,s \in S$, a solution $g \in G$ to $r^g = s$ can be thought of as a kind of logarithm. In this paper, we study the case where $G = S_n$, and develop analogs to the Shanks baby-step / giant-step procedure for ordinary discrete logarithms. Specifically, we compute two sets $A, B \subseteq S_n$ such that every permutation of $S_n$ can be written as a product $ab$ of elements $a \in A$ and $b \in B$. Our deterministic procedure is optimal up to constant factors, in the sense that $A$ and $B$ can be computed in optimal asymptotic complexity, and $|A|$ and $|B|$ are a small constant from $\sqrt{n!}$ in size. We also analyze randomized "collision" algorithms for the same problem

Unboxing Cluster Heatmaps

Background: Cluster heatmaps are commonly used in biology and related fields to reveal hierarchical clusters in data matrices. This visualization technique has high data density and reveal clusters better than unordered heatmaps alone. However, cluster heatmaps have known issues making them both time consuming to use and prone to error. We hypothesize that visualization techniques without the rigid grid constraint of cluster heatmaps will perform better at clustering-related tasks. Results: We developed an approach to “unbox” the heatmap values and embed them directly in the hierarchical clustering results, allowing us to use standard hierarchical visualization techniques as alternatives to cluster heatmaps. We then tested our hypothesis by conducting a survey of 45 practitioners to determine how cluster heatmaps are used, prototyping alternatives to cluster heatmaps using pair analytics with a computational biologist, and evaluating those alternatives with hour-long interviews of 5 practitioners and an Amazon Mechanical Turk user study with approximately 200 participants. We found statistically significant performance differences for most clustering-related tasks, and in the number of perceived visual clusters. Visit git.io/vw0t3 for our results. Conclusions: The optimal technique varied by task. However, gapmaps were preferred by the interviewed practitioners and outperformed or performed as well as cluster heatmaps for clustering-related tasks. Gapmaps are similar to cluster heatmaps, but relax the heatmap grid constraints by introducing gaps between rows and/or columns that are not closely clustered. Based on these results, we recommend users adopt gapmaps as an alternative to cluster heatmaps

HOw patients view extended half‐life products: impressions from real‐world experience (The HOPE study)

Introduction Extended half‐life (EHL) clotting factors have been shown to offer people with haemophilia (PwH) protection from bleeding with fewer infusions, which might reduce treatment burden. Aim The HOw Patients view Extended half‐life products (HOPE) study aimed to explore, understand and describe patient expectations around the prophylactic use of EHL products and to establish whether these expectations were met through individual follow‐up analysis. Methods The HOPE study was a prospective, qualitative cohort study conducted among PwH who had switched to Fc fusion protein EHL products in routine clinical care and who had not been recruited to clinical trials of these products. Semi‐structured audio‐recorded interviews were undertaken over two time points; transcripts were analysed to systematically generate theory from data that contains both inductive and deductive thinking. Results Forty‐three interviews were conducted with 25 participants. Most participants were positive about EHL treatment and intended to continue using them. Reduced frequency of infusions meant lives were less disrupted or dominated by haemophilia, and there was less perceived stress on overused veins. For those PwH who did not reduce infusion frequency, there were other perceived benefits from EHLs with respect to greater protection with higher trough levels and fewer bleeds. Conclusion Patients switching to EHL treatments believe these products will result in fewer infusions and less disruption of everyday life, leaving them feeling more protected with fewer bleeds and increased activity levels, as well as enhanced well‐being and mental health. Understanding patient expectation and experience around using products adds real‐world data to clinical trial experience

Variation in lung function as a marker of adherence to oral and inhaled medication in cystic fibrosis

Study aim: The aim of this study was to characterise adherence in an adult population with CF and to investigate if variation in lung function was a predictor of adherence to treatment. Patients and methods: Patients aged ≥ 16 years from an adult CF centre undertook adherence measures by medication possession ratio (MPR) and self-report and were assigned to one of three adherence categories (<50%, 50-<80%, 80% and above) by their composite score (MPR). Ordinal regression was used to identify predictors of adherence including coefficient variation measures for forced expiratory volume in 1 second (FEV1), weight and C-reactive protein, measured up to 6 and 12 months. Results: MPR data for 106 of 249 patients [mean age 29.8 (±9.2) years] was retrieved, indicating a mean adherence of 63%. Coefficient of variation FEV1 was inversely related to adherence and was a univariate predictor of adherence (6 months: 0.92 [0.87-0.98] p= 0.005 and 12 months: 0.94 [0.93-0.99], p=0.03]) and remained significant in the final models. The coefficient variation of weight and C-reactive protein were not predictive of adherence. Conclusions: Coefficient of variation FEV1 was identified as an objective predictor of adherence. Further evaluation of this potential marker of adherence is now required

“I wouldn't survive it, as simple as that”: Syndemic vulnerability among people living with chronic non-communicable disease during the COVID-19 pandemic

The co-occurrence of COVID-19, non-communicable diseases and socioeconomic disadvantage has been identified as creating a syndemic: a state of synergistic epidemics, occurring when co-occurring health conditions interact with social conditions to amplify the burden of disease. In this study, we use the concept of illness management work to explore the impact of the COVID-19 pandemic on the lives of people living with, often multiple, chronic health conditions in a range of social circumstances. In-depth interviews were conducted between May and July 2020 with 29 participants living in a city in North East England. Qualitative data provide unique insights for those seeking to better understand the consequences for human life and wellbeing of the interacting social, physical and psychological factors that create syndemic risks in people's lives. Among this group of people at increased vulnerability to harm from COVID-19, we find that the pandemic public health response increased the work required for condition management. Mental distress was amplified by fear of infection and by the requirements of social isolation and distancing that removed participants' usual sources of support. Social conditions, such as poor housing, low incomes and the requirement to earn a living, further amplified the work of managing everyday life and risked worsening existing mental ill health. As evidenced by the experiences reported here, the era of pandemics will require a renewed focus on the connection between health and social justice if stubborn, and worsening health and social inequalities are to be addressed or, at the very least, not increased

Systematic review and meta‐analysis of randomized controlled trials of psychological interventions to improve glycaemic control in children and adults with type 1 diabetes

Aim We conducted a systematic review aggregate and network meta‐analysis of psychological interventions for people with type 1 diabetes to assess their effectiveness in improving glycaemic levels. Methods We searched the following databases from 1 January 2003 to 1 July 2018: MEDLINE, CINAHL, PsycINFO, Embase, Cochrane Controlled Trials, Web of Science, clinicaltrials.gov, Dissertation Abstract International. We included randomized controlled trials (RCT) of psychological interventions for children and adults with type 1 diabetes reported in any language. We extracted data on publications, participant characteristics at baseline, intervention and control group, and data for the primary outcome, change in glycaemic control [HbA1c (mmol/mol/%)]. Study authors were contacted for missing data. The review was registered with international prospective register of systematic reviews registration (PROSPERO) CRD42016033619. Results Twenty‐four adult RCTs and 23 of children with type 1 diabetes were included in the systematic review. In aggregate meta‐analysis there was no overall effect of psychological intervention compared with control on HbA1c [adults, nine RCTs, n = 1102, pooled mean difference −0.12, 95% confidence intervals (CI) −0.27 to 0.03, I2 = 29.0%, P = 0.19; children, 20 RCTs, n = 2567, −0.09, 95% CI −0.22 to 0.04, I2=54.0% P=0.002]. Network meta‐analysis suggested that probability and rank‐ordering of effectiveness is highest for attention control groups (b = −0.47, 95% CI −0.80 to −0.12) followed by cognitive behavioural therapy (CBT) (−0.26, 95% CI −0.45 to −0.06) compared with usual care for adults. Conclusions Overall psychological interventions for children and adults with type 1 diabetes do not improve glycaemic control. For adults, CBT‐based interventions have the potential to be effective