TSrepr R package: Time Series Representations

Laurinec, Peter

doi:10.21105/joss.00577

Cited by 23 publications

(10 citation statements)

References 2 publications

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“…P-values were determined using two-tailed equal variance t-tests. Ca 2+ signaling and cAMP degradation profile analysis was conducted in R 1 using the TSrepr package (Laurinec, 2018). Data were first filtered for a positive increase in cAMP levels after bPAC stimulation by removing cells displaying a ∆F/F of less than 0.2.…”

Section: Discussionmentioning

confidence: 99%

Live-Cell Assays for Cell Stress Responses Reveal New Patterns of Cell Signaling Caused by Mutations in Rhodopsin, α-Synuclein and TDP-43

Harlen

Roush

Clayton

et al. 2019

Front. Cell. Neurosci.

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Many neurodegenerative diseases induce high levels of sustained cellular stress and alter a number of cellular processes. To examine how different mutations associated with neurodegenerative disease affect cell stress and signaling, we created live-cell assays for endoplasmic reticulum (ER)-mediated cell stress and second messenger signaling. We first examined neurodegenerative mutations associated with direct ER stress by exploring the effect of rhodopsin mutations on ER stress and Ca 2+ signaling. The rhodopsin P23H mutation, the most common mutation in autosomal dominant Retinitis Pigmentosa (RP), produced increased ER stress levels compared to wild type (WT) rhodopsin. Moreover, this increase in cell stress correlated with blunted Ca 2+ signaling in a stress-dependent manner. Analysis of single-cell Ca 2+ signaling profiles revealed unique Ca 2+ signaling responses exist in cells expressing WT or P23H rhodopsin, consistent with the idea that second messenger signaling is affected by cell stress. To explore the use of the ER-stress biosensor in neurodegenerative diseases that may not have a direct effect on ER-mediated cell stress, we examined how various mutants of α-synuclein and TDP-43 affected ER stress. Mutants of both α-synuclein and TDP-43 associated with Parkinson's disease (PD) and Amyotrophic lateral sclerosis (ALS) demonstrated increased ER stress compared to WT proteins. To examine the effect of α-synuclein and TDP-43 mutants on cellular signaling, we created a second live-cell assay to monitor changes in cAMP signaling during expression of various forms of α-synuclein and TDP-43. The increased cell stress caused by expression of the mutant proteins was accompanied by changes in phosphodiesterase activity. Both HEK293T and SH-SY5Y cells expressing these proteins displayed a shift towards increased cAMP degradation rates, likely due to increased phosphodiesterase activity. Together these data illustrate how biosensors for cellular stress and signaling can provide nuanced, new views of neurodegenerative disease processes.

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Section: Discussionmentioning

confidence: 99%

Live-Cell Assays for Cell Stress Responses Reveal New Patterns of Cell Signaling Caused by Mutations in Rhodopsin, α-Synuclein and TDP-43

Harlen

Roush

Clayton

et al. 2019

Front. Cell. Neurosci.

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show abstract

“…P-values were determined using two-tailed equal variance t-tests. Ca 2+ signaling and cAMP degradation profile analysis was conducted in R (www.r-project.org) using the TSrepr package (Laurinec, 2018). Data were first filtered for a positive increase in cAMP levels after bPAC stimulation by removing cells displaying a ΔF/F of less than 0.2.…”

Section: Discussionmentioning

confidence: 99%

Live-cell assays for cell stress responses reveal new patterns of cell signaling caused by mutations in rhodopsin, α-synuclein and TDP-43

Harlen

Roush

Clayton

et al. 2019

Preprint

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Many neurodegenerative diseases induce high levels of sustained cellular stress and alter a number of cellular processes. Genetically-encoded fluorescent biosensors are effective tools to examine neuronal activity and signaling in living cells. To examine how different mutations associated with neurodegenerative disease affect cell stress and signaling we created live-cell assays for ER-mediated cell stress and second messenger signaling. Analysis of the rhodopsin P23H mutation, the most common mutation in autosomal dominant Retinitis Pigmentosa, revealed increased cell stress levels compared to wild type rhodopsin. Moreover, this increase in cell stress correlated with blunted Ca 2+ signaling in a stress dependent manner. Analysis of single cell Ca 2+ signaling profiles revealed unique Ca 2+ signaling responses exist in cells expressing wild type or P23H mutants, further supporting the notion that second messenger signaling is affected by cell stress. To explore the use of the ER-stress biosensor in other neurodegenerative diseases we examined how various mutants of ɑ-synuclein and TDP-43 affected ER-mediated cell stress. Mutants of both ɑ-synuclein and TDP-43 associated with Parkinson's Disease and ALS demonstrated increases in ER-mediated cell stress. This increased cell stress was accompanied by changes in phosphodiesterase activity. Both HEK293T and SH-SY5Y cells expressing these proteins displayed a shift towards increased cAMP degradation rates, likely due to increased phosphodiesterase activity. Together these data illustrate how biosensors can provide nuanced, new views of neurodegenerative disease processes.

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“…Three time series representation techniques have been chosen because of their relatively low computation complexity covering three different categories: piecewise aggregate approximation (PAA) (non-data adaptive category) [34], symbolic aggregate approximation (SAX) (data adaptive) [35] and features based on clipping (data dictated) [36]. TSrep package in language R [37] has been used to implement these techniques. To compute the dissimilarity matrix, Euclidean distance is used on normalized values for PAA and clipping and Gower's distance for the non-numeric symbolic approach SAX [38].…”

Section: Block 2: Two-step Clusteringmentioning

confidence: 99%

Smart Meters Time Series Clustering for Demand Response Applications in the Context of High Penetration of Renewable Energy Resources

2021

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The variability in generation introduced in the electrical system by an increasing share of renewable technologies must be addressed by balancing mechanisms, demand response being a prominent one. In parallel, the massive introduction of smart meters allows for the use of high frequency energy use time series data to segment electricity customers according to their demand response potential. This paper proposes a smart meter time series clustering methodology based on a two-stage k-medoids clustering of normalized load-shape time series organized around the day divided into 48 time points. Time complexity is drastically reduced by first applying the k-medoids on each customer separately, and second on the total set of customer representatives. Further time complexity reduction is achieved using time series representation with low computational needs. Customer segmentation is undertaken with only four easy-to-interpret features: average energy use, energy–temperature correlation, entropy of the load-shape representative vector, and distance to wind generation patterns. This last feature is computed using the dynamic time warping distance between load and expected wind generation shape representative medoids. The two-stage clustering proves to be computationally effective, scalable and performant according to both internal validity metrics, based on average silhouette, and external validation, based on the ground truth embedded in customer surveys.

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TSrepr R package: Time Series Representations

Cited by 23 publications

References 2 publications

Live-Cell Assays for Cell Stress Responses Reveal New Patterns of Cell Signaling Caused by Mutations in Rhodopsin, α-Synuclein and TDP-43

Live-Cell Assays for Cell Stress Responses Reveal New Patterns of Cell Signaling Caused by Mutations in Rhodopsin, α-Synuclein and TDP-43

Live-cell assays for cell stress responses reveal new patterns of cell signaling caused by mutations in rhodopsin, α-synuclein and TDP-43

Smart Meters Time Series Clustering for Demand Response Applications in the Context of High Penetration of Renewable Energy Resources

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