AIGO: towards a unified framework for the analysis and the inter-comparison of GO functional annotations

BACKGROUND: In response to the rapid growth of available genome sequences, efforts have been made to develop automatic inference methods to functionally characterize them. Pipelines that infer functional annotation are now routinely used to produce new annotations at a genome scale and for a broad variety of species. These pipelines differ widely in their inference algorithms, confidence thresholds and data sources for reasoning. This heterogeneity makes a comparison of the relative merits of each approach extremely complex. The evaluation of the quality of the resultant annotations is also challenging given there is often no existing gold-standard against which to evaluate precision and recall. RESULTS: In this paper, we present a pragmatic approach to the study of functional annotations. An ensemble of 12 metrics, describing various aspects of functional annotations, is defined and implemented in a unified framework, which facilitates their systematic analysis and inter-comparison. The use of this framework is demonstrated on three illustrative examples: analysing the outputs of state-of-the-art inference pipelines, comparing electronic versus manual annotation methods, and monitoring the evolution of publicly available functional annotations. The framework is part of the AIGO library (http://code.google.com/p/aigo) for the Analysis and the Inter-comparison of the products of Gene Ontology (GO) annotation pipelines. The AIGO library also provides functionalities to easily load, analyse, manipulate and compare functional annotations and also to plot and export the results of the analysis in various formats. CONCLUSIONS: This work is a step toward developing a unified framework for the systematic study of GO functional annotations. This framework has been designed so that new metrics on GO functional annotations can be added in a very straightforward way

Representing and querying disease networks using graph databases

BACKGROUND: Systems biology experiments generate large volumes of data of multiple modalities and this information presents a challenge for integration due to a mix of complexity together with rich semantics. Here, we describe how graph databases provide a powerful framework for storage, querying and envisioning of biological data. RESULTS: We show how graph databases are well suited for the representation of biological information, which is typically highly connected, semi-structured and unpredictable. We outline an application case that uses the Neo4j graph database for building and querying a prototype network to provide biological context to asthma related genes. CONCLUSIONS: Our study suggests that graph databases provide a flexible solution for the integration of multiple types of biological data and facilitate exploratory data mining to support hypothesis generation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13040-016-0102-8) contains supplementary material, which is available to authorized users

Developing a complex intervention whilst considering implementation: the TANDEM (Tailored intervention for ANxiety and DEpression Management) intervention for patients with chronic obstructive pulmonary disease (COPD).

BACKGROUND: Guidelines now call for a thorough and comprehensive description of the development of healthcare interventions to aid evaluation and understanding of the processes of change. This was the primary aim of this study but we also recognised that effective interventions are commonly not implemented in clinical practice. It is suggested that insufficient attention is given to the implementation process at the development phase of interventions. This study outlines the 5 step iterative process we adopted for considering both implementation and effectiveness issues from the outset of intervention development. We use the development of a complex intervention Tailored intervention for ANxiety and DEpression Management (TANDEM) in patients with chronic obstructive pulmonary disease to illustrate this process. METHODS: Intervention development built upon the Medical Research Council framework for developing complex interventions and the person-based approach for development of behavioural interventions. Building an expert team, specifying theory, qualitative data collection and pre-piloting were all critical steps in our intervention development and are described here. RESULTS: Contact with experts in the field, and explicitly building on previous work, ensured efficiency of design. Qualitative work suggested guiding principles for the intervention such as introducing mood in relation to breathlessness, and providing flexible tailoring to patients' needs, whilst implementation principles focused on training selected respiratory professionals and requiring supervision to ensure standards of care. Subsequent steps of intervention development, pre-piloting and intervention refinement led to an intervention that was deemed acceptable and if successful will be ready for implementation. CONCLUSIONS: The TANDEM study was developed efficiently by building on previous work and considering implementation issues from the outset, with the aim that if shown to be effective it will have more rapid translation in to the health care system with accelerated patient benefits. TRIAL REGISTRATION: ISRCTN ISRCTN59537391 . Registered on 20 March 2017. Protocol version 6.0, 22 April 2018

Clustering of Pseudomonas aeruginosa transcriptomes from planktonic cultures, developing and mature biofilms reveals distinct expression profiles

BACKGROUND: Pseudomonas aeruginosa is a genetically complex bacterium which can adopt and switch between a free-living or biofilm lifestyle, a versatility that enables it to thrive in many different environments and contributes to its success as a human pathogen. RESULTS: Transcriptomes derived from growth states relevant to the lifestyle of P. aeruginosa were clustered using three different methods (K-means, K-means spectral and hierarchical clustering). The culture conditions used for this study were; biofilms incubated for 8, 14, 24 and 48 hrs, and planktonic culture (logarithmic and stationary phase). This cluster analysis revealed the existence and provided a clear illustration of distinct expression profiles present in the dataset. Moreover, it gave an insight into which genes are up-regulated in planktonic, developing biofilm and confluent biofilm states. In addition, this analysis confirmed the contribution of quorum sensing (QS) and RpoS regulated genes to the biofilm mode of growth, and enabled the identification of a 60.69 Kbp region of the genome associated with stationary phase growth (stationary phase planktonic culture and confluent biofilms). CONCLUSION: This is the first study to use clustering to separate a large P. aeruginosa microarray dataset consisting of transcriptomes obtained from diverse conditions relevant to its growth, into different expression profiles. These distinct expression profiles not only reveal novel aspects of P. aeruginosa gene expression but also provide a growth specific transcriptomic reference dataset for the research community

Targeting SLMAP-ALK—a novel gene fusion in lung adenocarcinoma

Assessment of ALK gene rearrangements is strongly recommended by the Molecular Testing Guideline for Selection of Lung Cancer Patients proposed by IASLC, AMP, and CAP at the time of diagnosis for patients with advanced stage disease. Non- small-cell lung cancer (NSCLC) with ALK gene rearrangements or the resulting fusion pro- teins have been, for the most part, successfully targeted with ALK tyrosine kinase inhibitors (TKIs). The most frequent rearrangement, the EML4-ALK oncogenic fusion, has more than 10 distinct variants, each with a discrete breakpoint in EML4. Recent studies have suggested that EML4-ALK variants may have differential responses to TKIs. Additionally, non-EML4- ALK fusions that result from ALK rearrangements with diverse 5′ partners could possibly have varied biologic and clinical implications in their therapeutic responses and outcomes of patients with NSCLC. Existing literature documents at least 20 non-EML4 fusion partners for ALK, and the clinical responsiveness to crizotinib ranges from increased sensitivity to re- sistance. This underscores the importance of identifying the precise 5′ fusion partner to ALK before initiation of therapy. Herein we report the identification of a novel SLMAP-ALK fusion in a patient with NSCLC

Infinitesimal incommensurate stripe phase in an axial next-nearest-neighbor Ising model in two dimensions

An axial next-nearest-neighbor Ising (ANNNI) model is studied by using the non-equilibrium relaxation method. We find that the incommensurate stripe phase between the ordered phase and the paramagnetic phase is negligibly narrow or may vanish in the thermodynamic limit. The phase transition is the second-order transition if approached from the ordered phase, and it is of the Kosterlitz-Thouless type if approached from the paramagnetic phase. Both transition temperatures coincide with each other within the numerical errors. The incommensurate phase which has been observed previously is a paramagnetic phase with a very long correlation length (typically $\xi\ge 500$). We could resolve this phase by treating very large systems ($\sim 6400\times 6400$), which is first made possible by employing the present method.Comment: 12 pages, 10 figures. To appear in Phys.Rev.

Tailored, psychological intervention for anxiety or depression in people with chronic obstructive pulmonary disease (COPD), TANDEM (Tailored intervention for ANxiety and DEpression Management in COPD): protocol for a randomised controlled trial

BACKGROUND: People with chronic obstructive pulmonary disease (COPD) are at increased risk of depression and anxiety, which greatly reduces their quality of life and is associated with worse outcomes; but these psychological co-morbidities are under-recognised and undertreated in COPD patients. Pulmonary rehabilitation (PR) improves mood for up to 6 months but health practitioners under-refer, and patients commonly fail to attend/complete PR. Research suggests that complex non-pharmacological interventions, including both psychological and exercise components, may reduce anxiety and depression in COPD. We have developed a tailored, cognitive behavioural approach (CBA) intervention for patients with COPD and co-morbid anxiety and/or depression ('TANDEM'), which precedes and optimises the benefits of currently offered PR. We hypothesise that such a psychological intervention, delivered by supervised, trained respiratory healthcare professionals, will improve mood in patients with mild to moderate anxiety and/or depression and encourage uptake and completion of PR. METHODS: We will conduct a multi-centre, pragmatic, randomised controlled trial of the TANDEM intervention compared to usual care across the Midlands, London, the South East and Bristol, UK. We will train healthcare professionals familiar with COPD to deliver the manualised, tailored, face-to-face, one-to-one intervention weekly for 6-8 weeks. We will recruit 430 participants from primary, community and secondary care with confirmed COPD and moderate to very severe airflow limitation, who are eligible for assessment for PR, and who screen positive for symptoms of mild/moderate depression and/or anxiety using the Hospital Anxiety and Depression scale (HADS). Participants will be randomised 1.25:1 (intervention: usual care). The co-primary outcomes are the HADS anxiety and depression subscale scores at 6 months; participants will be followed up to 12 months. Secondary outcomes include uptake and completion of PR and healthcare resource use. There will be a parallel process evaluation and a health economic evaluation. DISCUSSION: The TANDEM intervention has the potential to optimise the unrealised synergy between a psychological intervention and PR. The CBA sessions will precede PR and target individuals' cognitions, behaviours and symptoms associated with anxiety and depression to decrease psychological morbidity and increase effective self-management amongst patients with COPD. TRIAL REGISTRATION: ISRCTN, ID: ISRCTN59537391. Registered on 20 March 2017. Protocol version 6.0, 22 April 2018

EpiGeNet : A graph database of interdependencies between genetic and epigenetic events in colorectal cancer

The development of colorectal cancer (CRC)—the third most common cancer type—has been associated with deregulations of cellular mechanisms stimulated by both genetic and epigenetic events. StatEpigen is a manually curated and annotated database, containing information on interdependencies between genetic and epigenetic signals, and specialized currently for CRC research. Although StatEpigen provides a well-developed graphical user interface for information retrieval, advanced queries involving associations between multiple concepts can benefit from more detailed graph representation of the integrated data. This can be achieved by using a graph database (NoSQL) approach. Data were extracted from StatEpigen and imported to our newly developed EpiGeNet, a graph database for storage and querying of conditional relationships between molecular (genetic and epigenetic) events observed at different stages of colorectal oncogenesis. We illustrate the enhanced capability of EpiGeNet for exploration of different queries related to colorectal tumor progression; specifically, we demonstrate the query process for (i) stage-specific molecular events, (ii) most frequently observed genetic and epigenetic interdependencies in colon adenoma, and (iii) paths connecting key genes reported in CRC and associated events. The EpiGeNet framework offers improved capability for management and visualization of data on molecular events specific to CRC initiation and progression