Efficient change point detection for genomic sequences of continuous measurements

Muggeo, Vito M. R.; Adelfio, Giada

doi:10.1093/bioinformatics/btq647

Cited by 129 publications

(115 citation statements)

References 26 publications

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“…To more precisely determine the speed of the onset of the Lombard effect, we further analysed one exemplary element type from one individual (for which the most data were available) using a broken-line regression model fitted using the segmented package in R (Muggeo, 2008;Muggeo and Adelfio, 2010). This allowed us to precisely identify at what time after the onset of noise this element type was sung at a significantly higher sound pressure level than before the noise began.…”

Section: Statistical Analysesmentioning

confidence: 99%

Lombard effect onset times reveal the speed of vocal plasticity in a songbird

Hardman

Zollinger

Koselj

et al. 2017

Journal of Experimental Biology

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There was an error published in J. Exp. Biol. 220, 1065-1071.Eqn 2 was displayed incorrectly. The correct equation appears below.We apologise to the authors and readers for any inconvenience this may have caused. ABSTRACTAnimals that use vocal signals to communicate often compensate for interference and masking from background noise by raising the amplitude of their vocalisations. This response has been termed the Lombard effect. However, despite more than a century of research, little is known how quickly animals can adjust the amplitude of their vocalisations after the onset of noise. The ability to respond quickly to increases in noise levels would allow animals to avoid signal masking and ensure their calls continue to be heard, even if they are interrupted by sudden bursts of high-amplitude noise. We tested how quickly singing male canaries (Serinus canaria) exhibit the Lombard effect by exposing them to short playbacks of white noise and measuring the speed of their responses. We show that canaries exhibit the Lombard effect in as little as 300 ms after the onset of noise and are also able to increase the amplitude of their songs midsong and mid-phrase without pausing. Our results demonstrate high vocal plasticity in this species and suggest that birds are able to adjust the amplitude of their vocalisations very rapidly to ensure they can still be heard even during sudden changes in background noise levels.

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Section: Statistical Analysesmentioning

confidence: 99%

Lombard effect onset times reveal the speed of vocal plasticity in a songbird

Hardman

Zollinger

Koselj

et al. 2017

Journal of Experimental Biology

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“…Among a set of nonparametric models for multiple change points detection, models used in the changepoint, cpm and ecp packages in R serve as widely-used models for change detection, with proven effectiveness and efficiency in detecting anomalies in bioinformatics [43], transportation [44], finance [45], ecology [46], etc. Each of the nonparametric approaches has its pros and cons [47][48][49].…”

Section: Measuring Recovery Capabilitymentioning

confidence: 99%

Measuring Recovery to Build up Metrics of Flood Resilience Based on Pollutant Discharge Data: A Case Study in East China

Song

Huang

2017

Water

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Building "disaster-resilient" rather than "disaster-resistant" cities/communities requires the development of response capabilities to natural disasters and subsequent recovery. This study devises a new method to measure resilience via recovery capability to validate indicators from social, economic, infrastructural, and environmental domains. The pollutant discharge data (waste-water and waste-gas discharge/emission data) of local power plants, sewage treatment plants and main factories were used to monitor recovery process of both people's living and local industrial production as the waste water/gas is released irregularly during the short disaster-hit period. A time series analysis of such data was employed to detect the disturbance on these infrastructures from disasters and to assess community recovery capability. A recent record-breaking flash flood in Changzhou, a city in eastern-central China, was selected as a case study. We used ordinal logistic regression to identify leading proxies of flood resilience. A combination of six variables related to socioeconomic factors, infrastructure development and the environment, stood out and explained 61.4% of the variance in measured recovery capability. These findings substantiate the possibility of using recovery measurement based on pollutant discharge to validate resilience metrics, and contribute more solid evidences for policy-makers and urban planners to make corresponding measures for resilience enhancement.

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“…The simplest form of the piecewise linear model joins two straight lines at the threshold, whereas other forms incorporate a smooth zonal transition around the threshold and may be easier to fit if there is limited data near the threshold or if the estimated threshold converges on one of the observed data points (Toms andLesperance 2003, Toms 2012). Piecewise regression can also be used if the threshold is discontinuous, i.e., follows a step function, by first transforming the data using the cumulative sum (Muggeo and Adelfio 2011). Of great practical importance, it is possible to construct confidence intervals for the estimated threshold in this model (Toms and Lesperance 2003).…”

Section: Detecting Breakpoint-based Thresholdsmentioning

confidence: 99%

Threshold detection: matching statistical methodology to ecological questions and conservation planning objectives

Toms¹,

Villard²

2015

ACE

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ABSTRACT. Two types of ecological thresholds are now being widely used to develop conservation targets: breakpoint-based thresholds represent tipping points where system properties change dramatically, whereas classification thresholds identify groups of data points with contrasting properties. Both breakpoint-based and classification thresholds are useful tools in evidence-based conservation. However, it is critical that the type of threshold to be estimated corresponds with the question of interest and that appropriate statistical procedures are used to determine its location. On the basis of their statistical properties, we recommend using piecewise regression methods to identify breakpoint-based thresholds and discriminant analysis or classification and regression trees to identify classification thresholds. Détection des seuils : choix de la méthode statistique en fonction des questions écologiques et des objectifs de planification de la conservationRÉSUMÉ. À l'heure actuelle, deux types de seuils écologiques sont communément utilisés dans l'élaboration d'objectifs de conservation : alors que les seuils correspondant à un point de rupture représentent le point de basculement où les propriétés du système changent radicalement, les seuils de classification, eux, séparent les données en groupes ayant des propriétés divergentes. Tant les seuils fondés sur le point de rupture que ceux fondés sur la classification sont des outils utiles pour la conservation issue d'observations. Toutefois, le type de seuils que nous cherchons à estimer doit impérativement concorder avec la question qui nous préoccupe, tandis que la méthode statistique utilisée pour déterminer la localisation précise du seuil doit être appropriée. En nous fondant sur leurs propriétés statistiques, nous recommandons l'utilisation d'une méthode de régression par segments pour déterminer un seuil correspondant à un point de rupture et d'une analyse discriminante ou d'un arbre de classification ou de régression pour déterminer un seuil de classification.

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Efficient change point detection for genomic sequences of continuous measurements

Abstract: The methods described in this article are implemented in the new R package cumSeg available from the Comprehensive R Archive Network at http://CRAN.R-project.org/package=cumSeg.

Cited by 129 publications

References 26 publications

Lombard effect onset times reveal the speed of vocal plasticity in a songbird

Lombard effect onset times reveal the speed of vocal plasticity in a songbird

Measuring Recovery to Build up Metrics of Flood Resilience Based on Pollutant Discharge Data: A Case Study in East China

Threshold detection: matching statistical methodology to ecological questions and conservation planning objectives

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