scholarly journals Genome-wide circadian rhythm detection methods: systematic evaluations and practical guidelines

2020 ◽  
Author(s):  
Wenwen Mei ◽  
Zhiwen Jiang ◽  
Yang Chen ◽  
Li Chen ◽  
Aziz Sancar ◽  
...  
Keyword(s):  
Circadian Rhythm ◽  
Circadian Rhythms ◽  
Multiple Testing ◽  
Missing Values ◽  
Detection Methods ◽  
Genome Wide ◽  
Different Types ◽  
Practical Guidelines ◽  
Key Variables ◽  
Traditional Approaches

Abstract Circadian rhythms are oscillations of behavior, physiology and metabolism in many organisms. Recent advancements in omics technology make it possible for genome-wide profiling of circadian rhythms. Here, we conducted a comprehensive analysis of seven existing algorithms commonly used for circadian rhythm detection. Using gold-standard circadian and non-circadian genes, we systematically evaluated the accuracy and reproducibility of the algorithms on empirical datasets generated from various omics platforms under different experimental designs. We also carried out extensive simulation studies to test each algorithm’s robustness to key variables, including sampling patterns, replicates, waveforms, signal-to-noise ratios, uneven samplings and missing values. Furthermore, we examined the distributions of the nominal $P$-values under the null and raised issues with multiple testing corrections using traditional approaches. With our assessment, we provide method selection guidelines for circadian rhythm detection, which are applicable to different types of high-throughput omics data.

scholarly journals Genome-wide circadian rhythm detection methods: systematic evaluations and practical guidelines

2020 ◽  
Author(s):  
Wenwen Mei ◽  
Zhiwen Jiang ◽  
Yang Chen ◽  
Li Chen ◽  
Aziz Sancar ◽  
...  
Keyword(s):  
Circadian Rhythm ◽  
Gold Standard ◽  
Multiple Testing ◽  
Missing Values ◽  
Simulation Studies ◽  
Signal To Noise ◽  
Circadian Genes ◽  
Genome Wide ◽  
Different Types ◽  
Key Variables

ABSTRACTCircadian rhythms are oscillations of behavior, physiology, and metabolism in many organisms. Recent advancements in omics technology make it possible for genome-wide profiling of circadian rhythms. Here, we conducted a comprehensive analysis of seven existing algorithms commonly used for circadian rhythm detection. Using gold-standard circadian and non-circadian genes, we systematically evaluated the accuracy and reproducibility of the algorithms on empirical datasets generated from various omics platforms under different experimental designs. We also carried out extensive simulation studies to test each algorithm’s robustness to key variables, including sampling patterns, replicates, waveforms, signal-to-noise ratios, uneven samplings, and missing values. Furthermore, we examined the distributions of the nominal p-values under the null and raised issues with multiple testing corrections using traditional approaches. With our assessment, we provide method selection guidelines for circadian rhythm detection, which are applicable to different types of high-throughput omics data.Key pointsVarious methods have been developed for circadian rhythm detection on a genome-wide scale using omics technologies, yet there has not been a comprehensive summary and evaluation of all existing methods to date.Using gold-standard circadian and non-circadian genes, we systematically evaluated the accuracy and reproducibility of seven existing algorithms for circadian rhythm detection on empirical datasets generated from various omics platforms.We carried out extensive simulation studies to test each algorithm’s robustness to key variables, including sampling patterns, replicates, waveforms, signal-to-noise ratios, uneven samplings, and missing values.We examined the distributions of the nominal p-values under the null and raised issues with multiple testing corrections using the Benjamini-Hochberg procedure due to gene-gene correlation and testing being overly conservative.We provide method selection guidelines for circadian rhythm detection, which are applicable to different types of high-throughput omics data.

Missing Data - Better "Not to Have Them", but What If You Do? (Part 1)

Marketing ZFP ◽  
2019 ◽  
Vol 41 (4) ◽  
pp. 21-32
Author(s):  
Dirk Temme ◽  
Sarah Jensen
Keyword(s):  
Missing Data ◽  
Statistical Power ◽  
Missing Values ◽  
Graphical Representation ◽  
Marketing Research ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Full Information Maximum Likelihood ◽  
Definition Of ◽  
Traditional Approaches

Missing values are ubiquitous in empirical marketing research. If missing data are not dealt with properly, this can lead to a loss of statistical power and distorted parameter estimates. While traditional approaches for handling missing data (e.g., listwise deletion) are still widely used, researchers can nowadays choose among various advanced techniques such as multiple imputation analysis or full-information maximum likelihood estimation. Due to the available software, using these modern missing data methods does not pose a major obstacle. Still, their application requires a sound understanding of the prerequisites and limitations of these methods as well as a deeper understanding of the processes that have led to missing values in an empirical study. This article is Part 1 and first introduces Rubin’s classical definition of missing data mechanisms and an alternative, variable-based taxonomy, which provides a graphical representation. Secondly, a selection of visualization tools available in different R packages for the description and exploration of missing data structures is presented.

scholarly journals A novel GPU based intrusion detection system using deep autoencoder with Fruitfly optimization

2021 ◽  
Vol 3 (6) ◽  
Author(s):  
R. Sekhar ◽  
K. Sasirekha ◽  
P. S. Raja ◽  
K. Thangavel
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Missing Values ◽  
Detection System ◽  
Radial Basis Function Network ◽  
Detection Methods ◽  
Support Vector ◽  
Parameter Method ◽  
List Type ◽  
Fuzzy C Means

Abstract Intrusion Detection Systems (IDSs) have received more attention to safeguarding the vital information in a network system of an organization. Generally, the hackers are easily entering into a secured network through loopholes and smart attacks. In such situation, predicting attacks from normal packets is tedious, much challenging, time consuming and highly technical. As a result, different algorithms with varying learning and training capacity have been explored in the literature. However, the existing Intrusion Detection methods could not meet the desired performance requirements. Hence, this work proposes a new Intrusion Detection technique using Deep Autoencoder with Fruitfly Optimization. Initially, missing values in the dataset have been imputed with the Fuzzy C-Means Rough Parameter (FCMRP) algorithm which handles the imprecision in datasets with the exploit of fuzzy and rough sets while preserving crucial information. Then, robust features are extracted from Autoencoder with multiple hidden layers. Finally, the obtained features are fed to Back Propagation Neural Network (BPN) to classify the attacks. Furthermore, the neurons in the hidden layers of Deep Autoencoder are optimized with population based Fruitfly Optimization algorithm. Experiments have been conducted on NSL_KDD and UNSW-NB15 dataset. The computational results of the proposed intrusion detection system using deep autoencoder with BPN are compared with Naive Bayes, Support Vector Machine (SVM), Radial Basis Function Network (RBFN), BPN, and Autoencoder with Softmax. Article Highlights A hybridized model using Deep Autoencoder with Fruitfly Optimization is introduced to classify the attacks. Missing values have been imputed with the Fuzzy C-Means Rough Parameter method. The discriminate features are extracted using Deep Autoencoder with more hidden layers.

scholarly journals Time-restricted feeding regulates circadian rhythm of murine uterine clock

2021 ◽  
Author(s):  
Takashi Hosono ◽  
Masanori Ono ◽  
Takiko Daikoku ◽  
Michihiro Mieda ◽  
Satoshi Nomura ◽  
...  
Keyword(s):  
Circadian Rhythm ◽  
Circadian Rhythms ◽  
Protein Expression ◽  
Western Blot ◽  
Active Phase ◽  
Active Period ◽  
Restricted Feeding ◽  
Group Iii ◽  
Breakfast Skipping ◽  
Group I

Abstract Background Skipping breakfast is associated with dysmenorrhea in young women. This suggests that the delay of food intake in the active phase impairs uterine functions by interfering with circadian rhythms. Objective To examine the relationship between the delay of feeding and uterine circadian rhythms, we investigated the effects of the first meal occasion in the active phase on the uterine clock. Methods Zeitgeber time (ZT) was defined as ZT 0 (8:45) with lights on and ZT 12 (20:45) with lights off. Young female mice (8 weeks of age) were divided into 3 groups: group I (ad-libitum feeding), group II (time-restricted feeding during ZT12–16, initial 4 hours of the active period), and group III (time-restricted feeding during ZT20–24, last 4 hours of the active period, a breakfast-skipping model). After two weeks of dietary restriction, mice in each group were sacrificed at 4-hour intervals and the expression profiles of uterine clock genes, Bmal1, Per1, Per2, and Cry1, were examined. Results qPCR and Western blot analyses demonstrated synchronized circadian clock gene expression within the uterus. Immunohistochemical analysis confirmed that Bmal1 protein expression was synchronized among the endometrium and myometrium. In groups I and II, mRNA expression of Bmal1 was elevated after ZT12 at the start of the active phase. In contrast, Bmal1 expression was elevated just after ZT20 in group III, showing that the uterine clock rhythm had shifted 8 hours backward. The changes in Bmal1 protein expression were confirmed by Western blot analysis. Conclusion This study is the first to indicate that time-restricted feeding regulates a circadian rhythm of the uterine clock that is synchronized throughout the uterine body. These findings suggest that the uterine clock system is a new candidate to explain the etiology of breakfast skipping-induced uterine dysfunction.

scholarly journals Circadian Rhythm: Potential Therapeutic Target for Atherosclerosis and Thrombosis

2021 ◽  
Vol 22 (2) ◽  
pp. 676
Author(s):  
Andy W. C. Man ◽  
Huige Li ◽  
Ning Xia
Keyword(s):  
Circadian Rhythm ◽  
Cardiovascular Diseases ◽  
Circadian Rhythms ◽  
Circadian Clock ◽  
Therapeutic Target ◽  
Environmental Changes ◽  
Clock Genes ◽  
Vascular System ◽  
Peripheral Tissues ◽  
Inflammatory Processes

Every organism has an intrinsic biological rhythm that orchestrates biological processes in adjusting to daily environmental changes. Circadian rhythms are maintained by networks of molecular clocks throughout the core and peripheral tissues, including immune cells, blood vessels, and perivascular adipose tissues. Recent findings have suggested strong correlations between the circadian clock and cardiovascular diseases. Desynchronization between the circadian rhythm and body metabolism contributes to the development of cardiovascular diseases including arteriosclerosis and thrombosis. Circadian rhythms are involved in controlling inflammatory processes and metabolisms, which can influence the pathology of arteriosclerosis and thrombosis. Circadian clock genes are critical in maintaining the robust relationship between diurnal variation and the cardiovascular system. The circadian machinery in the vascular system may be a novel therapeutic target for the prevention and treatment of cardiovascular diseases. The research on circadian rhythms in cardiovascular diseases is still progressing. In this review, we briefly summarize recent studies on circadian rhythms and cardiovascular homeostasis, focusing on the circadian control of inflammatory processes and metabolisms. Based on the recent findings, we discuss the potential target molecules for future therapeutic strategies against cardiovascular diseases by targeting the circadian clock.

scholarly journals Detecting Toe-Off Events Utilizing a Vision-Based Method

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 329 ◽  
Author(s):  
Yunqi Tang ◽  
Zhuorong Li ◽  
Huawei Tian ◽  
Jianwei Ding ◽  
Bingxian Lin
Keyword(s):  
Wearable Sensors ◽  
Gait Pattern ◽  
Video Data ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Public Database ◽  
Video Frames ◽  
Different Types ◽  
Events Detection ◽  
Good Detection

Detecting gait events from video data accurately would be a challenging problem. However, most detection methods for gait events are currently based on wearable sensors, which need high cooperation from users and power consumption restriction. This study presents a novel algorithm for achieving accurate detection of toe-off events using a single 2D vision camera without the cooperation of participants. First, a set of novel feature, namely consecutive silhouettes difference maps (CSD-maps), is proposed to represent gait pattern. A CSD-map can encode several consecutive pedestrian silhouettes extracted from video frames into a map. And different number of consecutive pedestrian silhouettes will result in different types of CSD-maps, which can provide significant features for toe-off events detection. Convolutional neural network is then employed to reduce feature dimensions and classify toe-off events. Experiments on a public database demonstrate that the proposed method achieves good detection accuracy.

scholarly journals A powerful and efficient two-stage method for detecting gene-to-gene interactions in GWAS

Biostatistics ◽  
2017 ◽  
Vol 18 (3) ◽  
pp. 477-494 ◽  
Author(s):  
Jakub Pecanka ◽  
Marianne A. Jonker ◽  
Zoltan Bochdanovits ◽  
Aad W. Van Der Vaart ◽  
Keyword(s):  
Complex Traits ◽  
Multiple Testing ◽  
Statistical Power ◽  
Genome Wide Association Study ◽  
Score Test ◽  
Interaction Model ◽  
Type I ◽  
Two Stage ◽  
Genome Wide ◽  
Strong Control

Summary For over a decade functional gene-to-gene interaction (epistasis) has been suspected to be a determinant in the “missing heritability” of complex traits. However, searching for epistasis on the genome-wide scale has been challenging due to the prohibitively large number of tests which result in a serious loss of statistical power as well as computational challenges. In this article, we propose a two-stage method applicable to existing case-control data sets, which aims to lessen both of these problems by pre-assessing whether a candidate pair of genetic loci is involved in epistasis before it is actually tested for interaction with respect to a complex phenotype. The pre-assessment is based on a two-locus genotype independence test performed in the sample of cases. Only the pairs of loci that exhibit non-equilibrium frequencies are analyzed via a logistic regression score test, thereby reducing the multiple testing burden. Since only the computationally simple independence tests are performed for all pairs of loci while the more demanding score tests are restricted to the most promising pairs, genome-wide association study (GWAS) for epistasis becomes feasible. By design our method provides strong control of the type I error. Its favourable power properties especially under the practically relevant misspecification of the interaction model are illustrated. Ready-to-use software is available. Using the method we analyzed Parkinson’s disease in four cohorts and identified possible interactions within several SNP pairs in multiple cohorts.

Etudes comparées des rythmes circadiens et reflet actimétrique du sommeil de sportifs et de sédentaires en poste régulier de nuit

2003 ◽  
Vol 28 (6) ◽  
pp. 831-887 ◽  
Author(s):  
Benoît Mauvieux ◽  
Laurent Gouthière ◽  
Bruno Sesboüe ◽  
Damien Davenne
Keyword(s):  
Circadian Rhythm ◽  
Circadian Rhythms ◽  
Sleep Quality ◽  
Shift Work ◽  
Physical Training ◽  
Night Shift ◽  
Circadian Variation ◽  
Night Work ◽  
Sedentary Subjects

The aim of this study was to show the resistance and persistence of the circadian rhythm of temperature (T°) and the sleep quality of athletic subjects and sedentary subjects engaged in night work, and attempt to explain the mechanisms that influence these differences. The effects of night work on biological rhythms have been studied extensively in the past few years. The contradictory situations for the night workers irrefutably affect their biological systems. Individuals with high amplitudes in their circadian rhythms have been found to be more tolerant to shift work and this results in a greater stability of circadian rhythms. This seems beneficial in coping with frequent rhythm disturbances. The physical training program seems to improve several mechanisms of the human biological system: amplitudes of circadian rhythms were increased and the circadian rhythm period was more resistant to an environment extreme (night work, shift work, sleep deprivation, or jet lag). To test this hypothesis, athletes and sedentary subjects who were engaged in regular night work were selected in the PSA Peugeot Citroën Automobiles Group in French Normandy country. The circadian rhythm of the T° for both groups was studied with a specific methodology and with extensive spectral analysis, especially the spectral elliptic inverse method. Study models of the rhythm of the T° were determined and the characteristic parameters were exposed. A complementary actigraphic study showed the physical training program's effects on the sleep quality. The results revealed a large stability in the rhythm of circadian variation of T° for the athletes: the amplitude was still large but for the sedentary subjects the amplitude of the T° decreased and it was difficult to adjust a period on the rhythm of T°. The stability and persistent quality of the athletes' circadian rhythm was confirmed. We observed that the actigraphic sleep was greater for athletes than for sedentary subjects, and the acrophase time for the athletes was later than for the sedentary subjects during the night shift. Key words: circadian rhythm of temperature, actimetry, sleep quality, exercise, night work, methodology of rhythms analysis

scholarly journals Uncovering the mystery of opposite circadian rhythms between mouse and human leukocytes in humanized mice

Blood ◽  
2017 ◽  
Vol 130 (18) ◽  
pp. 1995-2005 ◽  
Author(s):  
Yue Zhao ◽  
Min Liu ◽  
Xue Ying Chan ◽  
Sue Yee Tan ◽  
Sharrada Subramaniam ◽  
...  
Keyword(s):  
Circadian Rhythm ◽  
Circadian Rhythms ◽  
Molecular Clock ◽  
Humanized Mice ◽  
Human Leukocytes ◽  
Clock Network ◽  
Key Points ◽  
Human And Mouse

Key Points Human circulating leukocytes in humanized mice reproduce similar circadian oscillations as seen in humans. A novel molecular clock network exhibiting opposite effects on regulating human and mouse leukocyte circadian rhythm is discovered.

scholarly journals Accuracy of probabilistic and deterministic record linkage: the case of tuberculosis

2016 ◽  
Vol 50 (0) ◽  
Author(s):  
Gisele Pinto de Oliveira ◽  
Ana Luiza de Souza Bierrenbach ◽  
Kenneth Rochel de Camargo Júnior ◽  
Cláudia Medina Coeli ◽  
Rejane Sobrino Pinheiro
Keyword(s):  
Record Linkage ◽  
Missing Values ◽  
Probabilistic Approach ◽  
Roc Curves ◽  
Cutoff Point ◽  
Accurate Analysis ◽  
Linkage Algorithm ◽  
Probabilistic Linkage ◽  
Key Variables ◽  
High Level

ABSTRACT OBJECTIVE To analyze the accuracy of deterministic and probabilistic record linkage to identify TB duplicate records, as well as the characteristics of discordant pairs. METHODS The study analyzed all TB records from 2009 to 2011 in the state of Rio de Janeiro. A deterministic record linkage algorithm was developed using a set of 70 rules, based on the combination of fragments of the key variables with or without modification (Soundex or substring). Each rule was formed by three or more fragments. The probabilistic approach required a cutoff point for the score, above which the links would be automatically classified as belonging to the same individual. The cutoff point was obtained by linkage of the Notifiable Diseases Information System – Tuberculosis database with itself, subsequent manual review and ROC curves and precision-recall. Sensitivity and specificity for accurate analysis were calculated. RESULTS Accuracy ranged from 87.2% to 95.2% for sensitivity and 99.8% to 99.9% for specificity for probabilistic and deterministic record linkage, respectively. The occurrence of missing values for the key variables and the low percentage of similarity measure for name and date of birth were mainly responsible for the failure to identify records of the same individual with the techniques used. CONCLUSIONS The two techniques showed a high level of correlation for pair classification. Although deterministic linkage identified more duplicate records than probabilistic linkage, the latter retrieved records not identified by the former. User need and experience should be considered when choosing the best technique to be used.

Sign in / Sign up

Export Citation Format

Share Document