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1.
Yi Chuan ; 41(9): 845-862, 2019 Sep 20.
Artigo em Chinês | MEDLINE | ID: mdl-31549683

RESUMO

Development of high-throughput sequencing stimulates a series of microbiome technologies, such as amplicon sequencing, metagenome, metatranscriptome, which have rapidly promoted microbiome research. Microbiome data analysis involves a lot of basic knowledge, software and databases, and it is difficult for peers to learn and select proper methods. This review systematically outlines the basic ideas of microbiome data analysis and the basic knowledge required to conduct analysis. In addition, it summarizes the advantages and disadvantages of commonly used software and databases used in the comparison, visualization, network, evolution, machine learning and association analysis. This review aims to provide a convenient and flexible guide for selecting analytical tools and suitable databases for mining the biological significance of microbiome data.


Assuntos
Análise de Dados , Microbiota , Bases de Dados Factuais , Sequenciamento de Nucleotídeos em Larga Escala , Metagenoma , Software
2.
BMC Bioinformatics ; 20(1): 463, 2019 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-31500569

RESUMO

BACKGROUND: The Human Protein Atlas (HPA) aims to map human proteins via multiple technologies including imaging, proteomics and transcriptomics. Access of the HPA data is mainly via web-based interface allowing views of individual proteins, which may not be optimal for data analysis of a gene set, or automatic retrieval of original images. RESULTS: HPAanalyze is an R package for retrieving and performing exploratory analysis of data from HPA. HPAanalyze provides functionality for importing data tables and xml files from HPA, exporting and visualizing data, as well as downloading all staining images of interest. The package is free, open source, and available via Bioconductor and GitHub. We provide examples of the use of HPAanalyze to investigate proteins altered in the deadly brain tumor glioblastoma. For example, we confirm Epidermal Growth Factor Receptor elevation and Phosphatase and Tensin Homolog loss and suggest the importance of the GTP Cyclohydrolase I/Tetrahydrobiopterin pathway. Additionally, we provide an interactive website for non-programmers to explore and visualize data without the use of R. CONCLUSIONS: HPAanalyze integrates into the R workflow with the tidyverse framework, and it can be used in combination with Bioconductor packages for easy analysis of HPA data.


Assuntos
Análise de Dados , Armazenamento e Recuperação da Informação , Proteínas de Neoplasias/metabolismo , Software , Encéfalo/metabolismo , Encéfalo/patologia , Neoplasias Encefálicas/metabolismo , Glioma/metabolismo , Humanos
3.
Psychiatr Prax ; 46(6): 317-323, 2019 Sep.
Artigo em Alemão | MEDLINE | ID: mdl-31408892

RESUMO

OBJECTIVE: Data on the quality and structure of outpatient care for adults with ADHD in Germany are scarce. The study describes the reality of care and identifies possible measures for improvement. METHOD: A complete survey of adults ≥ 18 years of age with a diagnosis of ADHD (ICD-Code F90.0) covered by statutory health insurance was carried out in the outpatient setting in the German Free State of Bavaria in 2012. RESULTS: The analysis revealed a diagnostic prevalence of ADHD in adults in Bavaria of 0.1 %, which was lower than expected based on ADHD prevalence estimates in the general population (about 3 %). Patients were diagnosed by specialists for CNS disorders and by general practitioners. About 30 % of patients received a medication approved for the treatment of ADHD, and these were in approx. 75 % of cases prescribed by specialists for CNS disorders. About 50 % of the patients received psychotherapy. CONCLUSION: General practitioners play an important role for medical care of adult patients with ADHD. Continuous medical education programmes and collaboration between general practitioners and specialists is an urgent imperative for improving outpatient care of ADHD in adults.


Assuntos
Assistência Ambulatorial/normas , Transtorno do Deficit de Atenção com Hiperatividade , Adulto , Transtorno do Deficit de Atenção com Hiperatividade/terapia , Análise de Dados , Alemanha , Humanos , Qualidade da Assistência à Saúde , Estudos Retrospectivos
5.
J Med Life ; 12(2): 160-167, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31406518

RESUMO

The prevalence of gestational diabetes mellitus (GDM) is increasing in Iran. Collection of patients' data is commonly conducted through using medical records. However, for providing a structured reporting based on the information needs, a minimum data set is a fast, inexpensive, and suitable method. For exchanging high-quality data between different healthcare centers and health monitoring organization, the data are required to be uniformly collected and registered. The present study aims at designing an MDS for creating the registry of GDM. The present study is an applied one, conducted in two stages, with a qualitative Delphi method in 2018. In the first stage of the study, it was attempted to extract the data elements of mothers with GDM, through reviewing the related studies and collecting these patients' data from the medical records. Then, based on the results of the first stage, a questionnaire including demographic, clinical, and pharmaceutical data was distributed among 20 individuals including gynecologists, pharmacists, nurses, and midwives. The validity of the questionnaire was examined by a team of experts and its reliability was examined by using Cronbach's alpha. Data analysis was conducted using descriptive statistics (frequency, percentage, and mean) and excel. An MDS of gestational diabetes mellitus was developed. This MDS divided into three categories: administrative, clinical, and pharmaceutical with 4, 18, and 2 sections and 35, 199, and 12 data elements, respectively. Determining the minimum data sets of GDM will be an effective step toward integrating and improving data management of patients with GDM. Moreover, it will be possible to store and retrieve the data related to these patients.


Assuntos
Análise de Dados , Diabetes Gestacional/epidemiologia , Sistema de Registros , Adulto , Técnica Delfos , Feminino , Humanos , Irã (Geográfico)/epidemiologia , Pessoa de Meia-Idade , Gravidez , Reprodutibilidade dos Testes , Inquéritos e Questionários , Adulto Jovem
6.
Stud Health Technol Inform ; 264: 35-39, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31437880

RESUMO

Clinical research studies often leverage various heterogeneous data sources including patient electronic health record, online survey, and genomic data. We introduce a graph-based, data integration and query tool called Carnival. We demonstrate its powerful ability to unify data from these disparate data sources to create datasets for two studies: prevalence and incidence case/control matches for coronary artery disease and controls for Marfan syndrome. We conclude with future directions for Carnival development.


Assuntos
Análise de Dados , Registros Eletrônicos de Saúde , Armazenamento e Recuperação da Informação , Estudos de Casos e Controles , Estudos de Coortes , Humanos
7.
Hum Genet ; 138(10): 1123-1142, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31312899

RESUMO

The study of runs of homozygosity (ROH) can shed light on population demographic history and cultural practices. We present a fine-scale ROH analysis of 1679 individuals from 28 sub-Saharan African (SSA) populations along with 1384 individuals from 17 worldwide populations. Using high-density SNP coverage, we could accurately identify ROH > 300 kb using PLINK software. The genomic distribution of ROH was analysed through the identification of ROH islands and regions of heterozygosity (RHZ). The analyses showed a heterogeneous distribution of autozygosity across SSA, revealing complex demographic histories. They highlight differences between African groups and can differentiate the impact of consanguineous practices (e.g. among the Somali) from endogamy (e.g. among several Khoe and San groups). Homozygosity cold and hotspots were shown to harbour multiple protein coding genes. Studying ROH therefore not only sheds light on population history, but can also be used to study genetic variation related to adaptation and potentially to the health of extant populations.


Assuntos
Grupo com Ancestrais do Continente Africano/genética , Genética Populacional , Homozigoto , África ao Sul do Saara , Consanguinidade , Cruzamentos Genéticos , Análise de Dados , Demografia , Variação Genética , Genômica/métodos , Geografia , Humanos
8.
Zhonghua Yu Fang Yi Xue Za Zhi ; 53(7): 744-751, 2019 Jul 06.
Artigo em Chinês | MEDLINE | ID: mdl-31288348

RESUMO

Cervical cancer has become an important disease that jeopardizes women's health, causing hundreds of thousands of new cases annually. Human papillomavirus (HPV) is the leading cause for cervical cancer. Since the world's first HPV vaccine was licensed in 2006, 92 countries around the world have introduced them in national immunization programs. The WHO recommends that scientific economic evaluation should be achieved before the introduction, but this is more difficult for low-and middle-income countries. Therefore, this article introduces a mathematical model recommended by WHO in 2014 to quickly and easily accomplish economic evaluation of HPV vaccine -the PRIME, and take the China's 2018 data published by International Agency for Research on Cancer (IARC) as an example. The evaluation result shows that the introduction of HPV vaccine in Chinese 12-year-old women is cost-effective.


Assuntos
Modelos Teóricos , Vacinas contra Papillomavirus/economia , Criança , China , Análise Custo-Benefício , Análise de Dados , Feminino , Humanos , Vacinas contra Papillomavirus/administração & dosagem , Neoplasias do Colo do Útero/prevenção & controle , Organização Mundial da Saúde
9.
Adv Exp Med Biol ; 1138: 137-162, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31313263

RESUMO

Medicine is among those research fields with a significant impact on humans and their health. Already for decades, medicine has established a tight coupling with the visualization domain, proving the importance of developing visualization techniques, designed exclusively for this research discipline. However, medical data is steadily increasing in complexity with the appearance of heterogeneous, multi-modal, multi-parametric, cohort or population, as well as uncertain data. To deal with this kind of complex data, the field of Visual Analytics has emerged. In this chapter, we discuss the many dimensions and facets of medical data. Based on this classification, we provide a general overview of state-of-the-art visualization systems and solutions dealing with high-dimensional, multi-faceted data. Our particular focus will be on multi-modal, multi-parametric data, on data from cohort or population studies and on uncertain data, especially with respect to Visual Analytics applications for the representation, exploration, and analysis of high-dimensional, multi-faceted medical data.


Assuntos
Pesquisa Biomédica , Gráficos por Computador , Análise de Dados , Humanos
10.
Nat Commun ; 10(1): 3045, 2019 07 10.
Artigo em Inglês | MEDLINE | ID: mdl-31292438

RESUMO

In order to advance precision medicine, detailed clinical features ought to be described in a way that leverages current knowledge. Although data collected from biomedical research is expanding at an almost exponential rate, our ability to transform that information into patient care has not kept at pace. A major barrier preventing this transformation is that multi-dimensional data collection and analysis is usually carried out without much understanding of the underlying knowledge structure. Here, in an effort to bridge this gap, Electronic Health Records (EHRs) of individual patients are connected to a heterogeneous knowledge network called Scalable Precision Medicine Oriented Knowledge Engine (SPOKE). Then an unsupervised machine-learning algorithm creates Propagated SPOKE Entry Vectors (PSEVs) that encode the importance of each SPOKE node for any code in the EHRs. We argue that these results, alongside the natural integration of PSEVs into any EHR machine-learning platform, provide a key step toward precision medicine.


Assuntos
Análise de Dados , Coleta de Dados/métodos , Aprendizado de Máquina não Supervisionado , Pesquisa Biomédica/estatística & dados numéricos , Registros Eletrônicos de Saúde/estatística & dados numéricos , Medicina de Precisão/métodos
11.
BMC Health Serv Res ; 19(1): 439, 2019 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-31262280

RESUMO

BACKGROUND: Research suggested that waiting time and consultation time are associated with overall patient satisfaction concerning health services. However, there is a lack of information regarding this subject in Latin American countries, where particular aspects of health systems and population characteristics could modify this association. Our aim was to evaluate the association of waiting time and consultation time with patient satisfaction, in Peruvian ambulatory care facilities and propose a cut-off points of waiting and consultation time based on patient satisfaction. METHODS: Cross-sectional secondary data analysis of the National Survey on User Satisfaction of Health Services (ENSUSALUD-2015), a national-wide survey with a probabilistic sample of 181 Peruvian ambulatory care facilities. Patient satisfaction, waiting time, consultation time, and sociodemographic variables were collected from the ENSUSALUD-2015. All variables were collected by survey directly to patients, from the selected ambulatory care facilities, after their consultation. Complex survey sampling was considered for data analysis. In the association analysis, we grouped the waiting time and consultation time variables, every 10 min, because for it is more relevant and helpful in the statistical and practical interpretation of the results, instead of the every-minute unit. RESULTS: The survey was performed in 13,360 participants. Response rate were 99.8 to 100% in the main variables. Waiting time (for every 10 min) was inversely associated with patient satisfaction (aOR: 0.98, 95% CI: 0.97-0.99), although the aOR was lower among those who reported a waiting time ≤ 90 min (aOR: 0.92, 95% CI: 0.89-0.96). Consultation time (for every 10 min) was directly associated with patient satisfaction (aOR: 1.59, 95% CI: 1.26-2.01), although the aOR was higher among those who reported a consultation time ≤ 15 min (aOR: 2.31, 95% CI: 1.66-3.21). CONCLUSION: In Peruvian ambulatory care facilities, both waiting time and consultation time showed an association with overall patient satisfaction, which was stronger in the first 90 min of waiting time and in the first 15 min of consultation time. This should be taken into consideration when designing interventions to improve waiting times and consultation times in ambulatory care facilities from Peru or from similar contexts.


Assuntos
Instituições de Assistência Ambulatorial/estatística & dados numéricos , Satisfação do Paciente/estatística & dados numéricos , Encaminhamento e Consulta/estatística & dados numéricos , Adulto , Estudos Transversais , Análise de Dados , Feminino , Humanos , Masculino , Peru/epidemiologia
12.
Nat Commun ; 10(1): 3069, 2019 07 23.
Artigo em Inglês | MEDLINE | ID: mdl-31337762

RESUMO

While rich medical, behavioral, and socio-demographic data are key to modern data-driven research, their collection and use raise legitimate privacy concerns. Anonymizing datasets through de-identification and sampling before sharing them has been the main tool used to address those concerns. We here propose a generative copula-based method that can accurately estimate the likelihood of a specific person to be correctly re-identified, even in a heavily incomplete dataset. On 210 populations, our method obtains AUC scores for predicting individual uniqueness ranging from 0.84 to 0.97, with low false-discovery rate. Using our model, we find that 99.98% of Americans would be correctly re-identified in any dataset using 15 demographic attributes. Our results suggest that even heavily sampled anonymized datasets are unlikely to satisfy the modern standards for anonymization set forth by GDPR and seriously challenge the technical and legal adequacy of the de-identification release-and-forget model.


Assuntos
Análise de Dados , Anonimização de Dados , Informações Pessoalmente Identificáveis , Conjuntos de Dados como Assunto , Funções Verossimilhança , Distribuição Normal
14.
Nat Commun ; 10(1): 3018, 2019 07 09.
Artigo em Inglês | MEDLINE | ID: mdl-31289270

RESUMO

The analysis of whole-genome sequencing studies is challenging due to the large number of noncoding rare variants, our limited understanding of their functional effects, and the lack of natural units for testing. Here we propose a scan statistic framework, WGScan, to simultaneously detect the existence, and estimate the locations of association signals at genome-wide scale. WGScan can analytically estimate the significance threshold for a whole-genome scan; utilize summary statistics for a meta-analysis; incorporate functional annotations for enhanced discoveries in noncoding regions; and enable enrichment analyses using genome-wide summary statistics. Based on the analysis of whole genomes of 1,786 phenotypically discordant sibling pairs from the Simons Simplex Collection study for autism spectrum disorders, we derive genome-wide significance thresholds for whole genome sequencing studies and detect significant enrichments of regions showing associations with autism in promoter regions, functional categories related to autism, and enhancers predicted to regulate expression of autism associated genes.


Assuntos
Transtorno do Espectro Autista/genética , Análise de Dados , Genoma Humano/genética , Modelos Genéticos , Algoritmos , Conjuntos de Dados como Assunto , Feminino , Regulação da Expressão Gênica , Estudo de Associação Genômica Ampla/métodos , Humanos , Masculino , Fenótipo , Polimorfismo de Nucleotídeo Único , Irmãos , Sequenciamento Completo do Genoma/métodos
15.
Nat Commun ; 10(1): 3015, 2019 07 09.
Artigo em Inglês | MEDLINE | ID: mdl-31289271

RESUMO

The protein-protein interaction (PPI) network of an organism serves as a skeleton for its signaling circuitry, which mediates cellular response to environmental and genetic cues. Understanding this circuitry could improve the prediction of gene function and cellular behavior in response to diverse signals. To realize this potential, one has to comprehensively map PPIs and their directions of signal flow. While the quality and the volume of identified human PPIs improved dramatically over the last decade, the directions of these interactions are still mostly unknown, thus precluding subsequent prediction and modeling efforts. Here we present a systematic approach to orient the human PPI network using drug response and cancer genomic data. We provide a diffusion-based method for the orientation task that significantly outperforms existing methods. The oriented network leads to improved prioritization of cancer driver genes and drug targets compared to the state-of-the-art unoriented network.


Assuntos
Biologia Computacional/métodos , Neoplasias/genética , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas/efeitos dos fármacos , Análise de Dados , Bases de Dados Genéticas/estatística & dados numéricos , Bases de Dados de Produtos Farmacêuticos/estatística & dados numéricos , Conjuntos de Dados como Assunto , Humanos , Mapas de Interação de Proteínas/genética , Software
16.
Nat Commun ; 10(1): 3066, 2019 07 11.
Artigo em Inglês | MEDLINE | ID: mdl-31296857

RESUMO

Metagenomic sequence classification should be fast, accurate and information-rich. Emerging long-read sequencing technologies promise to improve the balance between these factors but most existing methods were designed for short reads. MetaMaps is a new method, specifically developed for long reads, capable of mapping a long-read metagenome to a comprehensive RefSeq database with >12,000 genomes in <16 GB or RAM on a laptop computer. Integrating approximate mapping with probabilistic scoring and EM-based estimation of sample composition, MetaMaps achieves >94% accuracy for species-level read assignment and r2 > 0.97 for the estimation of sample composition on both simulated and real data when the sample genomes or close relatives are present in the classification database. To address novel species and genera, which are comparatively harder to predict, MetaMaps outputs mapping locations and qualities for all classified reads, enabling functional studies (e.g. gene presence/absence) and detection of incongruities between sample and reference genomes.


Assuntos
Biologia Computacional/métodos , Análise de Dados , Metagenômica/métodos , Algoritmos , Conjuntos de Dados como Assunto , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Metagenoma/genética , Microbiota/genética , Análise de Sequência de DNA/métodos , Software
17.
Stud Health Technol Inform ; 262: 55-58, 2019 Jul 04.
Artigo em Inglês | MEDLINE | ID: mdl-31349264

RESUMO

The last four decades witnessed a huge progress in digitizing health information, representing an unmatched opportunity for utilizing health analytics in improving the quality of healthcare and reducing its costs. To learn more about different challenges facing the successful utilization of health analytics, a careful review of literature was conducted, and a qualitative analysis was used to explore and classify these challenges. Three main categories of challenges were identified. 1) Technological challenges; hardware, software, and data content, 2) Human challenges; knowledge, experiences, beliefs and attitudes, and end user behaviors, and 3) Organizational challenges; managerial, financial, and legal barriers to optimal utilization of health analytics. The non-technological problems seem to be harder to solve as well as more time consuming, including the existence of a specific business need and a clear vision to guide the project. In addition, health analytics should always be built with the end users in mind.


Assuntos
Assistência à Saúde , Registros Eletrônicos de Saúde , Análise de Dados , Humanos
18.
Stud Health Technol Inform ; 262: 105-109, 2019 Jul 04.
Artigo em Inglês | MEDLINE | ID: mdl-31349277

RESUMO

Correct choice and administration of a statistical test are absolutely essential for meaningful interpretation of research data, yet mistakes are still frequent and could be easily found in published scientific papers or PhD theses. The aim of this study was to analyze mistakes made by PhD students in statistical analysis of data collected during research within the framework of their thesis. PhD students frequently use Excel and SPSS for data processing, while SAS, Stata and R are also available. The study was designed as cross-sectional analysis of random sample (n=15) of PhD theses in pre-approval stage at Faculty of Medical Sciences, University of Kragujevac, Serbia. In total 14 (93%) theses had at least one mistake. The most frequent mistakes were as the following: insufficient statistical power due to small sample size, inappropriate presentation of results at tables and graphs, andinappropriate choice of statistical tests. In order to improve the situation, training courses in statistics during PhD studies should be re-evaluated and improved in regard to relevance, delivery methods and motivating potential, and mentors should invest more effort to review the data and guide students through statistical analysis.


Assuntos
Mentores , Estudantes , Estudos Transversais , Análise de Dados , Humanos , Sérvia , Software
19.
Stud Health Technol Inform ; 262: 180-183, 2019 Jul 04.
Artigo em Inglês | MEDLINE | ID: mdl-31349296

RESUMO

Optimal antibiotic use for the treatment of nosocomial infections plays a central role in the effort to control the rapidly increasing prevalence of multidrug-resistant bacteria. Antibiotic selection should be based on accurate knowledge of local susceptibility rates. Traditional methods of resistance reporting, which are in routine use by microbiology laboratories could be enhanced by using statistically significant results. We present a method of reporting based on antibiotic susceptibility data analysis which offers an accurate tool that reduces clinician uncertainty and enables optimization of the antibiotic selection process.


Assuntos
Infecção Hospitalar , Análise de Dados , Farmacorresistência Bacteriana , Klebsiella pneumoniae , Antibacterianos/farmacologia , Farmacorresistência Bacteriana Múltipla , Humanos , Klebsiella pneumoniae/efeitos dos fármacos
20.
Stud Health Technol Inform ; 262: 332-335, 2019 Jul 04.
Artigo em Inglês | MEDLINE | ID: mdl-31349335

RESUMO

Adverse Childhood Experiences (ACEs) are negative events or states that affect children, with lasting impacts throughout their adulthood. ACES are considered one of the major risk factors for several adverse health outcomes and are associated with low quality of life and many detrimental social and economic consequences. In order to enact better surveillance of ACEs and their associated conditions, it is instrumental to provide tools to detect, monitor and respond effectively. In this paper, we present a recommender system tasked with simplifying data collection, access, and reasoning related to ACEs. The recommender system uses both semantic and statistical methods to enable content and context-based filtering.


Assuntos
Experiências Adversas da Infância , Análise de Dados , Qualidade de Vida , Adulto , Criança , Humanos , Fatores de Risco
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