cLoops2: a full-stack comprehensive analytical tool for chromatin interactions

Investigating chromatin interactions between regulatory regions such as enhancer and promoter elements is vital for a deeper understanding of gene expression regulation. The emerging 3D mapping technologies focusing on enriched signals such as Hi-TrAC/TrAC-looping, compared to Hi-C and variants, reduce the sequencing cost and provide higher interaction resolution for cis-regulatory elements. A robust pipeline is needed for the comprehensive interpretation of these data, especially for loop-centric analysis. Therefore, we have developed a new versatile tool named cLoops2 for the full-stack analysis of the 3D chromatin interaction data. cLoops2 consists of core modules for peak-calling, loop-calling, differentially enriched loops calling and loops annotation. Additionally, it also contains multiple modules to carry out interaction resolution estimation, data similarity estimation, features quantification and aggregation analysis, and visualization. cLoops2 with documentation and example data are open source and freely available at GitHub: https://github.com/YaqiangCao/cLoops2.

Ticagrelor in unstable carotid stenosis - a case report

Introduction. Ticagrelor is an oral, reversible, direct-acting inhibitor of adenosine diphosphate receptor P2Y12, which has a faster onset of action and stronger inhibition of platelet aggregation than clopidogrel. Case Report. This case report describes a 54-year-old male patient with repeated, transient ischemic attacks due to ipsilateral, significant carotid stenosis registered by carotid duplex ultrasound. In addition to aspirin, clopidogrel and rosuvastatin were added to the therapy. Despite optimal treatment, the patient was continuously unstable with frequent but transient neurological symptoms. A magnetic resonance imaging of the brain showed acute, cortical-subcortical ischemic lesions in the left frontal and parietal lobes, while the computed tomography angiography of the endocranium showed progression of findings and occlusion of the left common carotid artery. Subsequently, laboratory platelet aggregation analysis confirmed aspirin resistance and poor response to clopidogrel. Episodes of transient ischemic attacks were stabilized after the exclusion of dual antiplatelet therapy and introduction of ticagrelor. After that, the patient?s symptoms did not recur and he remained stable. Conclusion. The incidence of resistance to antiplatelet therapy in patients with stroke or transient ischemic attack varies greatly and ranges from 3% to 85% for aspirin, and 28% to 44% for clopidogrel. Our case showed that platelet aggregation analysis is reasonable if patients with transient ischemic attack or minor acute ischemic stroke are neurologically unstable, despite optimal medical treatment and when other therapeutic options, such as carotid revascularization, are not indicated. In such situations, ticagrelor may be a suitable alternative to dual antiplatelet therapy.

A Differentially Private Hybrid Approach to Traffic Monitoring

In recent years, privacy research has been gaining ground in vehicular communication technologies. Collecting data from connected vehicles presents a range of opportunities for industry and government to perform data analytics. Although many researchers have explored some privacy solutions for vehicular communications, the conditions to deploy them are still maturing, especially when it comes to privacy for sensitive data aggregation analysis. In this work, we propose a hybrid solution combining the original differential privacy framework with an instance-based additive noise technique. The results show that for typical instances we obtain a significant reduction in outliers. As far as we know, our paper is the first detailed experimental evaluation of differentially private techniques applied to traffic monitoring. The validation of the proposed solution was performed through extensive simulations in typical traffic scenarios using real data.

Open Source Software (OSS) for Big Data

This chapter discusses Open Source Software and associated technologies for the processing of Big Data. This includes discussions of Hadoop-related projects, the current top open source data tools and frameworks such as SMACK that is acronym for open source technologies Spark, Mesos, Akka, Cassandra, and Kafka that together compose the ingestion, aggregation, analysis, and storage layers for Big Data processing. Tabular summaries and categories for 38 Open Source Statistical Software (OSSS) are provided that include for each listing of features and URLs for free downloads. The current challenges of Big Data and Open Source Software are also discussed.

COVID-19 pandemic in Yemen: A questionnaire based survey, what do we know?

Introduction: Coronavirus infectious disease 2019 (COVID-19) is currently one of the most important public health crises affecting the global human population. It continues to spread widely, as the world still lacks specific treatments and a vaccine for the virus. The scenario of COVID-19 in Yemen seems obscure due to the lack of adequate data, therefore, we developed an electronic questionnaire and distributed it online among Yemeni people. The aim of this study was to understand the COVID-19 epidemiological situation in Yemen better since there is currently limited published data and limited availability of COVID-19 testing. Methodology: A 34-question web-based survey was distributed on social media outlets targeting people in Yemen. Data aggregation, analysis, and visualization were performed using Tableau and Microsoft Excel. Results: 2,341 individuals reported symptoms concerning for COVID-19 infection, with 25.4% reporting a chronic medical condition. Diabetes, hypertension, asthma, and immune deficiency were associated with increased severity of the disease, while obesity, cardiovascular disease, kidney disease, and liver disease were not. Only 37 individuals (1.6%) had a confirmatory COVID-19 PCR test. The presence of high fever, dyspnea, chest pain, and dysphagia were symptoms that tended to be correlated to worse clinical outcomes. Conclusions: This study provides some important information about the early overspread of COVID-19 within the Yemeni community in May, June, and July of 2020. It shows that online questionnaires may help in collecting data about pandemics in resource-limited countries where testing availability is limited.

Family aggregation analysis shows a possible heritable background of equine grass sickness (dysautonomia) in a Hungarian stud population

Equine grass sickness (also known as dysautonomia) is a life-threatening polyneuropathic disease affecting horses with approx. 80% mortality. Since its first description over a century ago, several factors, such as the phenotype, intestinal microbiome, environment, management and climate, have been supposed to be associated with the increased risk of dysautonomia. In this retrospective study, we examined the possible involvement of genetic factors. Medical and pedigree datasets regarding 1,233 horses with 49 affected animals born during a 23-year period were used in the analysis. Among the descendants of some stallions, the proportion of animals diagnosed with dysautonomia was unexpectedly high. Among males, the odds of dysautonomia were found to be higher, albeit not significantly, than among females. Significant familial clustering (genealogical index of familiality, P = 0.001) was observed among the affected animals. Further subgroups were identified with significant (P < 0.001) aggregation among close relatives using kinship-based methods. Our analysis, along with the slightly higher disease frequency in males, suggests that dysautonomia may have a genetic causal factor with an X-linked recessive inheritance pattern. This is the first study providing ancestry data and suggesting a heritable component in the likely multifactorial aetiology of the disease.