Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 59.608
Filtrar
1.
Methods Mol Biol ; 2212: 347-376, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33733367

RESUMEN

As practitioners, we aim to provide a consolidated introduction of tidy data science along with routine packages for relational data representation and interpretation, with the focus on analytics related to human genetic interactions. We describe three showcases (also made available at https://23verse.github.io/gini ), all done so via the R one-liner, in this chapter defined as a sequential pipeline of elementary functions chained together achieving a complex task. We guide the readers through step-by-step instructions on (case 1) performing network module analysis of genetic interactions, followed by visualization and interpretation; (case 2) implementing a practical strategy of how to identify and interpret tissue-specific genetic interactions; and (case 3) carrying out interaction-based tissue clustering and differential interaction analysis. All showcases demonstrate simplistic beauty and efficient nature of this analytics. We anticipate that mastering a dozen of one-liners to efficiently interpret genetic interactions is very timely now; opportunities for computational translational research are arising for data scientists to harness therapeutic potential of human genetic interaction data that are ever-increasingly available.


Asunto(s)
Algoritmos , Ciencia de los Datos/estadística & datos numéricos , Epistasis Genética , Redes Reguladoras de Genes , Programas Informáticos , Animales , Proteína BRCA1/genética , Proteína BRCA1/metabolismo , Proteína BRCA2/genética , Proteína BRCA2/metabolismo , Interpretación Estadística de Datos , Genoma Humano , Genotipo , Humanos , Ratones , Especificidad de Órganos , Fenotipo , Poli(ADP-Ribosa) Polimerasa-1/genética , Poli(ADP-Ribosa) Polimerasa-1/metabolismo , Mapeo de Interacción de Proteínas
2.
BMC Bioinformatics ; 22(1): 107, 2021 Mar 04.
Artículo en Inglés | MEDLINE | ID: mdl-33663372

RESUMEN

BACKGROUND: Visual exploration of gene product behavior across multiple omic datasets can pinpoint technical limitations in data and reveal biological trends. Still, such exploration is challenging as there is a need for visualizations that are tailored for the purpose. RESULTS: The OmicLoupe software was developed to facilitate visual data exploration and provides more than 15 interactive cross-dataset visualizations for omics data. It expands visualizations to multiple datasets for quality control, statistical comparisons and overlap and correlation analyses, while allowing for rapid inspection and downloading of selected features. The usage of OmicLoupe is demonstrated in three different studies, where it allowed for detection of both technical data limitations and biological trends across different omic layers. An example is an analysis of SARS-CoV-2 infection based on two previously published studies, where OmicLoupe facilitated the identification of gene products with consistent expression changes across datasets at both the transcript and protein levels. CONCLUSIONS: OmicLoupe provides fast exploration of omics data with tailored visualizations for comparisons within and across data layers. The interactive visualizations are highly informative and are expected to be useful in various analyses of both newly generated and previously published data. OmicLoupe is available at quantitativeproteomics.org/omicloupe.


Asunto(s)
Biología Computacional/instrumentación , Descubrimiento del Conocimiento , Programas Informáticos , /genética , Interpretación Estadística de Datos , Humanos , Proteoma , Transcriptoma
3.
Neuron ; 109(5): 751-766, 2021 03 03.
Artículo en Inglés | MEDLINE | ID: mdl-33596406

RESUMEN

Human and non-human animal behavior is highly malleable and adapts successfully to internal and external demands. Such behavioral success stands in striking contrast to the apparent instability in neural activity (i.e., variability) from which it arises. Here, we summon the considerable evidence across scales, species, and imaging modalities that neural variability represents a key, undervalued dimension for understanding brain-behavior relationships at inter- and intra-individual levels. We believe that only by incorporating a specific focus on variability will the neural foundation of behavior be comprehensively understood.


Asunto(s)
Conducta , Encéfalo/fisiología , Neuronas/fisiología , Animales , Conducta Animal , Interpretación Estadística de Datos , Humanos
5.
Am J Public Health ; 111(4): 704-707, 2021 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-33600247

RESUMEN

Objectives. To determine the number of excess deaths (i.e., those exceeding historical trends after accounting for COVID-19 deaths) occurring in Florida during the COVID-19 pandemic.Methods. Using seasonal autoregressive integrated moving average time-series modeling and historical mortality trends in Florida, we forecasted monthly deaths from January to September of 2020 in the absence of the pandemic. We compared estimated deaths with monthly recorded total deaths (i.e., all deaths regardless of cause) during the COVID-19 pandemic and deaths only from COVID-19 to measure excess deaths in Florida.Results. Our results suggest that Florida experienced 19 241 (15.5%) excess deaths above historical trends from March to September 2020, including 14 317 COVID-19 deaths and an additional 4924 all-cause, excluding COVID-19, deaths in that period.Conclusions. Total deaths are significantly higher than historical trends in Florida even when accounting for COVID-19-related deaths. The impact of COVID-19 on mortality is significantly greater than the official COVID-19 data suggest.


Asunto(s)
/mortalidad , Causas de Muerte/tendencias , Interpretación Estadística de Datos , Florida , Humanos , Modelos Estadísticos , Estudios Retrospectivos
6.
JMIR Public Health Surveill ; 7(2): e20335, 2021 02 15.
Artículo en Inglés | MEDLINE | ID: mdl-33481755

RESUMEN

BACKGROUND: In Japan, as a countermeasure against the COVID-19 outbreak, both the national and local governments issued voluntary restrictions against going out from residences at the end of March 2020 in preference to the lockdowns instituted in European and North American countries. The effect of such measures can be studied with mobility data, such as data which is generated by counting the number of requests made to Apple Maps for directions in select countries/regions, sub-regions, and cities. OBJECTIVE: We investigate the associations of mobility data provided by Apple Inc and an estimate an an effective reproduction number R(t). METHODS: We regressed R(t) on a polynomial function of daily Apple data, estimated using the whole period, and analyzed subperiods delimited by March 10, 2020. RESULTS: In the estimation results, R(t) was 1.72 when voluntary restrictions against going out ceased and mobility reverted to a normal level. However, the critical level of reducing R(t) to <1 was obtained at 89.3% of normal mobility. CONCLUSIONS: We demonstrated that Apple mobility data are useful for short-term prediction of R(t). The results indicate that the number of trips should decrease by 10% until herd immunity is achieved and that higher voluntary restrictions against going out might not be necessary for avoiding a re-emergence of the outbreak.


Asunto(s)
Número Básico de Reproducción , Teléfono Celular , Brotes de Enfermedades , Vigilancia en Salud Pública/métodos , Interpretación Estadística de Datos , Humanos , Japón/epidemiología , Reproducibilidad de los Resultados
7.
Neural Netw ; 135: 158-176, 2021 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-33388507

RESUMEN

The sparse coding algorithm has served as a model for early processing in mammalian vision. It has been assumed that the brain uses sparse coding to exploit statistical properties of the sensory stream. We hypothesize that sparse coding discovers patterns from the data set, which can be used to estimate a set of stimulus parameters by simple readout. In this study, we chose a model of stereo vision to test our hypothesis. We used the Locally Competitive Algorithm (LCA), followed by a naïve Bayes classifier, to infer stereo disparity. From the results we report three observations. First, disparity inference was successful with this naturalistic processing pipeline. Second, an expanded, highly redundant representation is required to robustly identify the input patterns. Third, the inference error can be predicted from the number of active coefficients in the LCA representation. We conclude that sparse coding can generate a suitable general representation for subsequent inference tasks.


Asunto(s)
Algoritmos , Interpretación Estadística de Datos , Reconocimiento de Normas Patrones Automatizadas/métodos , Disparidad Visual/fisiología , Percepción Visual/fisiología , Teorema de Bayes , Humanos , Visión Ocular/fisiología , Corteza Visual/fisiología
9.
Viruses ; 13(1)2021 Jan 19.
Artículo en Inglés | MEDLINE | ID: mdl-33478139

RESUMEN

The first step of cellular entry for the human immunodeficiency virus type-1 (HIV-1) occurs through the binding of its envelope protein (Env) with the plasma membrane receptor CD4 and co-receptor CCR5 or CXCR4 on susceptible cells, primarily CD4+ T cells and macrophages. Although there is considerable knowledge of the molecular interactions between Env and host cell receptors that lead to successful fusion, the precise way in which HIV-1 receptors redistribute to sites of virus binding at the nanoscale remains unknown. Here, we quantitatively examine changes in the nanoscale organisation of CD4 on the surface of CD4+ T cells following HIV-1 binding. Using single-molecule super-resolution imaging, we show that CD4 molecules are distributed mostly as either individual molecules or small clusters of up to 4 molecules. Following virus binding, we observe a local 3-to-10-fold increase in cluster diameter and molecule number for virus-associated CD4 clusters. Moreover, a similar but smaller magnitude reorganisation of CD4 was also observed with recombinant gp120. For one of the first times, our results quantify the nanoscale CD4 reorganisation triggered by HIV-1 on host CD4+ T cells. Our quantitative approach provides a robust methodology for characterising the nanoscale organisation of plasma membrane receptors in general with the potential to link spatial organisation to function.


Asunto(s)
Antígenos CD4/metabolismo , Membrana Celular/metabolismo , Membrana Celular/virología , VIH-1/fisiología , Imagen Individual de Molécula/métodos , Linfocitos T/metabolismo , Linfocitos T/virología , Acoplamiento Viral , Algoritmos , Anticuerpos Monoclonales , Línea Celular , Interpretación Estadística de Datos , Proteína gp120 de Envoltorio del VIH/metabolismo , Interacciones Huésped-Patógeno , Humanos , Procesamiento de Imagen Asistido por Computador , Unión Proteica , Receptores CCR5/metabolismo , Receptores del VIH/metabolismo
10.
Am J Clin Nutr ; 113(3): 517-524, 2021 03 11.
Artículo en Inglés | MEDLINE | ID: mdl-33515017

RESUMEN

The use of classic nonparametric tests (cNPTs), such as the Kruskal-Wallis and Mann-Whitney U tests, in the presence of unequal variance for between-group comparisons of means and medians may lead to marked increases in the rate of falsely rejecting null hypotheses and decreases in statistical power. Yet, this practice remains prevalent in the scientific literature, including nutrition and obesity literature. Some nutrition and obesity studies use a cNPT in the presence of unequal variance (i.e., heteroscedasticity), sometimes because of the mistaken rationale that the test corrects for heteroscedasticity. Herein, we discuss misconceptions of using cNPTs in the presence of heteroscedasticity. We then discuss assumptions, purposes, and limitations of 3 common tests used to test for mean differences between multiple groups, including 2 parametric tests: Fisher's ANOVA and Welch's ANOVA; and 1 cNPT: the Kruskal-Wallis test. To document the impact of heteroscedasticity on the validity of these tests under conditions similar to those used in nutrition and obesity research, we conducted simple simulations and assessed type I error rates (i.e., false positives, defined as incorrectly rejecting the null hypothesis). We demonstrate that type I error rates for Fisher's ANOVA, which does not account for heteroscedasticity, and Kruskal-Wallis, which tests for differences in distributions rather than means, deviated from the expected significance level. Greater deviation from the expected type I error rate was observed as the heterogeneity increased, especially in the presence of an imbalanced sample size. We provide brief tutorial guidance for authors, editors, and reviewers to identify appropriate statistical tests when test assumptions are violated, with a particular focus on cNPTs.


Asunto(s)
Interpretación Estadística de Datos , Ciencias de la Nutrición/estadística & datos numéricos , Obesidad/dietoterapia , Estadísticas no Paramétricas , Humanos , Reproducibilidad de los Resultados
11.
Cancer Imaging ; 21(1): 9, 2021 Jan 08.
Artículo en Inglés | MEDLINE | ID: mdl-33419476

RESUMEN

BACKGROUND: The prognostic value of 18F-FDG PET/CT in extranodal natural killer/T-cell lymphoma (ENKTL) is not well established. We aimed to develop nomograms for individualized estimates of progression-free survival (PFS) and overall survival (OS) in patients with ENKTL using 18F-FDG PET/CT parameters and clinical parameters. METHODS: A total of 171 patients with newly diagnosed ENKTL undergoing 18F-FDG PET/CT scanning were retrospectively analyzed. Nomograms were constructed according to multivariate Cox proportional hazards regression. The predictive and discriminatory capacities of the nomograms were then measured using the concordance index (C-index), calibration plots, and Kaplan-Meier curves. The C-index, the area under receiver operating characteristic (ROC) curve (AUC), and decision curve analysis (DCA) were used to contrast the predictive and discriminatory capacities of the nomograms against with the International Prognostic Index (IPI) and Korean Prognostic Index (KPI). RESULTS: Multivariate analysis demonstrated that pretreatment SUVmax≥9.5, disease stage II and III-IV, elevated lactate dehydrogenase (LDH), and elevated ß2-microglobulin (ß2-MG) had the strongest association with unfavorable PFS and OS. In addition, hemoglobin (Hb) < 120 g/L had a tendency to be associated with PFS. Both nomogram models incorporated SUVmax, Ann Arbor stage, LDH, and ß2-MG. The PFS nomogram also included Hb. The nomograms showed good prediction accuracies, with the C-indexes for PFS and OS were 0.729 and 0.736, respectively. The calibration plots for 3-year and 5-year PFS/OS reported good consistency between predicted and observed probabilities for survival time. The PFS and OS were significantly different according to tertiles of nomogram scores (p < 0.001). The C-index and AUCs of the nomograms were higher than that of IPI and KPI. Moreover, DCA showed that the predictive accuracy of the nomograms for PFS and OS were both higher than that of IPI and KPI. CONCLUSIONS: This study established nomograms that incorporate pretreatment SUVmax and clinical parameters, which could be effective tools for individualized prognostication of both PFS and OS in patients with newly diagnosed ENKTL.


Asunto(s)
Procesamiento de Imagen Asistido por Computador/métodos , Linfoma Extranodal de Células NK-T/diagnóstico por imagen , Nomogramas , Tomografía Computarizada por Tomografía de Emisión de Positrones/métodos , Adulto , Anciano , Interpretación Estadística de Datos , Progresión de la Enfermedad , Supervivencia sin Enfermedad , Femenino , Fluorodesoxiglucosa F18 , Humanos , Estimación de Kaplan-Meier , Células Asesinas Naturales/patología , Linfoma Extranodal de Células NK-T/mortalidad , Linfoma Extranodal de Células NK-T/patología , Masculino , Persona de Mediana Edad , Análisis Multivariante , Estadificación de Neoplasias , Valor Predictivo de las Pruebas , Modelos de Riesgos Proporcionales , Curva ROC , Radiofármacos , Estándares de Referencia , Estudios Retrospectivos
13.
Sensors (Basel) ; 21(2)2021 Jan 13.
Artículo en Inglés | MEDLINE | ID: mdl-33451092

RESUMEN

São Paulo is the most populous state in Brazil, home to around 22% of the country's population. The total number of Covid-19-infected people in São Paulo has reached more than 1 million, while its total death toll stands at 25% of all the country's fatalities. Joining the Brazilian academia efforts in the fight against Covid-19, in this paper we describe a unified framework for monitoring and forecasting the Covid-19 progress in the state of São Paulo. More specifically, a freely available, online platform to collect and exploit Covid-19 time-series data is presented, supporting decision-makers while still allowing the general public to interact with data from different regions of the state. Moreover, a novel forecasting data-driven method has also been proposed, by combining the so-called Susceptible-Infectious-Recovered-Deceased model with machine learning strategies to better fit the mathematical model's coefficients for predicting Infections, Recoveries, Deaths, and Viral Reproduction Numbers. We show that the obtained predictor is capable of dealing with badly conditioned data samples while still delivering accurate 10-day predictions. Our integrated computational system can be used for guiding government actions mainly in two basic aspects: real-time data assessment and dynamic predictions of Covid-19 curves for different regions of the state. We extend our analysis and investigation to inspect the virus spreading in Brazil in its regions. Finally, experiments involving the Covid-19 advance in other countries are also given.


Asunto(s)
/epidemiología , Brasil/epidemiología , Interpretación Estadística de Datos , Predicción , Humanos , Aprendizaje Automático , /aislamiento & purificación
14.
Sci Rep ; 11(1): 2147, 2021 01 25.
Artículo en Inglés | MEDLINE | ID: mdl-33495534

RESUMEN

We analyze data from Twitter to uncover early-warning signals of COVID-19 outbreaks in Europe in the winter season 2019-2020, before the first public announcements of local sources of infection were made. We show evidence that unexpected levels of concerns about cases of pneumonia were raised across a number of European countries. Whistleblowing came primarily from the geographical regions that eventually turned out to be the key breeding grounds for infections. These findings point to the urgency of setting up an integrated digital surveillance system in which social media can help geo-localize chains of contagion that would otherwise proliferate almost completely undetected.


Asunto(s)
/epidemiología , Monitoreo Epidemiológico , Pandemias/prevención & control , Medios de Comunicación Sociales/estadística & datos numéricos , /prevención & control , Interpretación Estadística de Datos , Europa (Continente)/epidemiología , Predicción/métodos , Humanos , Pandemias/estadística & datos numéricos , Denuncia de Irregularidades
15.
Life Sci ; 269: 119093, 2021 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-33476630

RESUMEN

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a severe public health problem around the globe. Various epidemiological, statistical, and laboratory-based studies have shown that the role of temperature and other environmental factors has important influence in the transmission of coronaviruses. Scientific research is needed to answer the questions about the spread and transmission of the infection, whether people could be avoided from being infected with COVID-19 in next summer. AIM: We aim to investigate the association of daily average temperature, daily average dew point, daily average humidity, daily average wind speed, and daily average pressure with the infection caused by this novel coronavirus in Pakistan. KEY FINDINGS: First, we check the correlation between environmental factors and daily infected cases of COVID-19; among them, temperature and dew point have positive linear relationship with daily infected cases of COVID-19. The thought-provoking findings of the present study suggested that higher temperature and dew point can contribute to a rise in COVID-19 disease in four provinces of Pakistan, possible to genome modifications and viral resistance to harsh environment. Moreover, it is also observed that humidity in Punjab and Sindh, and wind speed in Balochistan and Khyber Pakhtunkhwa have influenced the spreading of daily infected COVID-19 cases. SIGNIFICANCE: Current study will serve as a guideline to develop understanding of environmental factors that influence COVID-19 spread, helping policymakers to prepare and handle a catastrophe resulting from this pandemic.


Asunto(s)
/epidemiología , Temperatura , Tiempo (Meteorología) , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Interpretación Estadística de Datos , Femenino , Humanos , Humedad , Masculino , Persona de Mediana Edad , Pakistán/epidemiología , Viento , Adulto Joven
16.
Methods Mol Biol ; 2194: 77-105, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32926363

RESUMEN

Survival analysis is tremendously powerful, and is a popular methodology for analyzing time to event models in bioinformatics. Furthermore, several of its extensions can simultaneously perform variable selection in conjunction with model estimation. While this flexibility is extremely desirable, under certain scenarios, binary class variable selection and classification methods might provide more reliable risk estimates. Synthetic simulations and real data case studies suggest that when (1) randomly censored points comprise only a small portion of data, (2) biological markers are weak, (3) it is desired to compute risk across predetermined time intervals, and (4) the assumptions of the competing time to event models are violated, binary class models tend to perform superior. In practice, it might be prudent to test both model families to guarantee adequate analysis. Here we describe the pipeline of binary class feature selection and classification for time to event risk assessment.


Asunto(s)
Bioestadística/métodos , Biología Computacional/métodos , Neoplasias/mortalidad , Algoritmos , Análisis de Varianza , Simulación por Computador , Interpretación Estadística de Datos , Análisis Discriminante , Humanos , Modelos Lineales , Pronóstico , Medición de Riesgo/métodos , Máquina de Vectores de Soporte , Análisis de Supervivencia
17.
Methods Mol Biol ; 2194: 177-186, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32926367

RESUMEN

Tumor heterogeneity can arise from a variety of extrinsic and intrinsic sources and drives unfavorable outcomes. With recent technological advances, single-cell RNA sequencing has become a way for researchers to easily assay tumor heterogeneity at the transcriptomic level with high resolution. However, ongoing research focuses on different ways to analyze this big data and how to compare across multiple different samples. In this chapter, we provide a practical guide to calculate inter- and intrasample diversity metrics from single-cell RNA sequencing datasets. These measures of diversity are adapted from commonly used metrics in statistics and ecology to quantify and compare sample heterogeneity at single-cell resolution.


Asunto(s)
Biología Computacional/métodos , Perfilación de la Expresión Génica/métodos , Heterogeneidad Genética , Neoplasias/genética , Análisis de Secuencia de ARN/métodos , Análisis de la Célula Individual/métodos , Interpretación Estadística de Datos , Progresión de la Enfermedad , Humanos , Control de Calidad , Programas Informáticos
18.
Methods Mol Biol ; 2194: 143-175, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32926366

RESUMEN

High-throughput sequencing (HTS) has revolutionized researchers' ability to study the human transcriptome, particularly as it relates to cancer. Recently, HTS technology has advanced to the point where now one is able to sequence individual cells (i.e., "single-cell sequencing"). Prior to single-cell sequencing technology, HTS would be completed on RNA extracted from a tissue sample consisting of multiple cell types (i.e., "bulk sequencing"). In this chapter, we review the various bioinformatics and statistical methods used in the processing, quality control, and analysis of bulk and single-cell RNA sequencing methods. Additionally, we discuss how these methods are also being used to study tumor heterogeneity.


Asunto(s)
Biología Computacional/métodos , Neoplasias/genética , Análisis de Secuencia de ARN/métodos , Análisis de la Célula Individual/métodos , Interpretación Estadística de Datos , Bases de Datos Genéticas , Perfilación de la Expresión Génica , Humanos , Control de Calidad , Neoplasias Cutáneas/genética
19.
Methods Mol Biol ; 2237: 263-276, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33237426

RESUMEN

When obtaining high-throughput data from antibody arrays, researchers have to face a couple of questions: How and by what means can they get reasonable results significant to their research from these data? Similar to a gene microarray, the classical statistical pipeline of an antibody array includes data preprocessing transformation, differential expression analysis, classification, and biological annotation analysis. In this chapter, we will provide a pipeline of statistical approaches suitable for antibody arrays to facilitate better understanding of the results gained from each of these steps.


Asunto(s)
Aprendizaje Automático , Análisis por Matrices de Proteínas/métodos , Animales , Interpretación Estadística de Datos , Humanos , Inmunoensayo/métodos
20.
Methods Mol Biol ; 2237: 277-314, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33237427

RESUMEN

In this chapter, we introduce the application of R, a statistical programming language in the analysis of antibody array data. We start from a brief introduction of R itself and then cover data filtration and transformation, data visualization, differential expression analysis with/without variance correction, co-expression network, functional enrichment analysis, and statistical modeling.


Asunto(s)
Análisis por Matrices de Proteínas/métodos , Programas Informáticos/normas , Animales , Interpretación Estadística de Datos , Conjuntos de Datos como Asunto , Humanos , Inmunoensayo/métodos
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA
...