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publicNov 2018View details →

Data from: Functional traits and community composition: a comparison among community-weighted means, weighted correlations, and multilevel models

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publicNov 2024View details →

Niche modelling and correlation analyses of climate variables

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publicAug 2022View details →

Multi-omic brain and behavioral correlates of cell-free fetal DNA methylation in macaque maternal obesity models (NMR datasets, maternal plasma and infant brain)

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publicOct 2020View details →

Protea repens whole transcriptome count data for control and drought treatment for 8 populations, climatic data for the 8 populations and phenotypic data collected, and data used for linear mixed models for climate gene expression/trait correlation testing

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opencc-byJun 2020View details →

Ionospheric Horizontal Correlation Length Derived From IRI-2016 Model Errors

Ionospheric horizontal correlation length based on IRI-2016 model and JPL Global Ionospheric Maps. This metadata can be used for the construction of the covariance matrix for ionospheric data assimilation. each .nc file corresponds to one bin.  Binning in season (winter, summer, equinox): 00=month 1,2,11,12 01=month 5,6,7,8 02=month 3,4,9,10                     Binning in F10.7 solar flux (low, moderate, high): 00=0-100 s.f.u 01=100-150 s.f.u. 02=150-350 s.f.u.                                                  Binning in UT: 2-h frames.  Example:  The name of the .nc file:        Corr_Length_IRI_seazon_01_sf_00_UT_18.nc    would correspond to summer season, low solar flux, 18-20 UT.  Inside of the .nc files: longitudes=array of geomagnetic longitudes (degrees) latitudes=array of geomagnetic latitudes (degrees) zonal_corr_length=array of size (nlon, nlat), is a map of zonal correlation lengths merid_corr_length=array of size (nlon, nlat), is a map of meridional correlation lengths L_4d=array of size (nlon, nlat, 4), is a map of correlation lengths in 4 perpendicular azimuthal directions; 0=0 deg, 1=90 deg, 2=180 deg, 3=-90 deg L_az=array of size (nlon, nlat, 36), is a map of correlation lengths in 36 azimuthal directions (0,10,20,30,...,350 deg)

opencc-zeroAug 2020View details →

Correlated and geographically predictable Neanderthal and Denisovan legacies are difficult to reconcile with a simple model based on inter-breeding

Although the presence of archaic hominin legacies in humans is taken for granted, little attention has been given as to how the data fit with how humans colonised the world. Here I show that Neanderthal and Denisovan legacies are strongly correlated and that, like heterozygosity, distance from Africa predicts legacy size. Simulations confirm that, once created, legacy size is extremely stable: it may reduce through admixture with lower legacy populations but cannot increase detectably through neutral drift. Consequently, populations carrying the highest legacies must also be those whose ancestors inter-bred most with archaics. However, the populations with the highest legacies are globally scattered and are unified, not by having origins within the known Neanderthal range, but instead by living in locations that lie furthest from Africa. Furthermore, the Simons Genome Diversity Project data reveal two very distinct correlations between Neanderthal and Denisovan legacies, one that starts in North Africa and increases west to east across Eurasia and into some parts of Oceania, and a second, much steeper trend that starts in Africa, peaking with the San and Ju/'hoansi and which, if extrapolated, predicts the large inferred legacies of both archaics found in Oceania / Australia. These trends are difficult to reconcile with classical models of how introgression occurred but may fit a speculative model in which the loss of diversity that occurred when humans moved further from Africa created a gradient in heterozygosity that in turn progressively reduced mutation rate such that populations furthest from Africa have diverged less from our common ancestor and hence from the archaics. The two distinct trends could be interpreted in terms of two 'out of Africa' events, an early one ending in Oceania and Australia and a later one that colonised Eurasia and the Americas.

opencc-zeroNov 2020View details →

Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect

Aim Correlative Species Distribution Models (SDMs) are subject to substantial spatio-temporal limitations when historical occurrence records of data-poor species provide incomplete and outdated information for niche modelling. Complementary mechanistic modelling techniques can, therefore, offer a valuable contribution to underpin more physiologically-informed predictions of biological invasions, the risk of which is often exacerbated by climate change. In this study we integrate physiological and human pressure data to address the uncertainties and limitations of correlative SDMs and to better understand, predict, and manage biological invasions. Location Western archipelagos of the Southern Ocean and martime Antarctica Taxon Eretmoptera murphyi (Chironomidae), invertebrates. Methods Mahalanobis Distances were used for correlative SDM construction for a species with few records. A mechanistic SDM was built around different fitness components (larval survival and life stage progression) as a function of temperature. SDM predictions were combined with human activity levels in Antarctica to generate a site vulnerability index to the colonization of E. murphyi. Future scenarios of ecophysiological suitability were built around the warming trends in the region. Results Both SDMs converge to predict high environmental suitability in the species' native and introduced ranges. However, the mechanistic model indicates a slightly larger invasive potential based on larval performance at different temperatures. Human activity levels across the Antarctic Peninsula play a key role in discerning site vulnerabilities. Niche suitability in Antarctica grows considerably under long-term climate scenarios, leading to a substantially higher invasive threat to the Antarctic ecosystems. In turn changing conditions result on growing physiological mismatches with the environment in the native range on South Georgia. Main conclusions Long-term studies of invasion potential under climate benefit from integrating correlative predictions with physiological experiments, as the invasion potential varies depending on the area and the timescale examined. This study also highlights a conservation paradox whereby the accidental introduction of an insect represents a threat to the Antarctic ecoystems that contrasts with its endangered status at the native range.

opencc-zeroDec 2015View details →

Data from: Is there a correlation between abundance and environmental suitability derived from ecological niche modelling? A meta-analysis

It is thought that species abundance is correlated with environmental suitability and that environmental variables, scale, and type of model fitting can confound this relationship. We performed a meta-analysis to (i) test whether species abundance is positively correlated with environmental suitability derived from correlative ecological niche models (ENM), (ii) test whether studies encompassing large areas within a species range (>50%) exhibited higher AS correlations than studies encompassing small areas within a species range (<50%), (iii) assess which modelling method provided higher AS correlation, and (iv) compare strength of the AS relationship between studies using only climatic variables and those that used both climatic and other environmental variables to derive suitability. We used correlation coefficients to measure the relationship between abundance and environmental suitability derived from ENM. Each correlation coefficient was considered an effect size in a random-effects multivariate meta-analysis. In all cases we found a significantly positive relationship between abundance and suitability. This relationship was consistent regardless of scale of study, ENM method, or set of variables used to derive suitability. There was no difference in strength of correlation between studies focusing on large or small areas within a species' range or among ENM methods. Studies using other variables in combination with climate exhibited higher AS correlations than studies using only climatic variables. We conclude that occurrence data can be a reasonable proxy for abundance, especially for vertebrates, and the use of local variables increases the strength of the AS relationship. Use of ENMs can significantly decrease survey costs and allow the study of large-scale abundance patterns using less information. Including only climatic variables in ENM may confound the relationship between abundance and suitability when compared to studies including variables taken locally. However, modelers and conservationists must be aware that high environmental suitability does not always indicate high abundance.

opencc-zeroDec 2017View details →

Data from: Serial homology and correlated characters in morphological phylogenetics: modeling the evolution of dental crests in placentals

Accurate modeling of the complexity of morphological evolution is crucial for morphological phylogenetics and for performing tests on a wide variety of evolutionary scenarios. In this context, morphological integration and the problem of correlated categorical characters represent a major challenge. In particular, the magnitude and implications of correlations among serially homologous structures such as teeth have been much debated but were never tested statistically within a broad phylogenetic context. Here, we present a large-scale empirical study analyzing the serial variation of cingular crests on successive molars (M1, M2 and M3) of 274 placental species in a phylogenetic context. Both likelihood analyses and analysis of phylogenetic co-distributions demonstrated highly correlated evolution in the entire sample and thus the non-independence of these serial features at a macroevolutionary scale. Likelihood analyses show that their serial variation should be better scored within a single composite character model with constrained paths for transitions enabling simultaneous changes on all three molars, which suggests a strong developmental or genetic integration. These results are congruent with current molecular and developmental knowledge related to dental morphological variation and call into question the frequent use of separate characters scored on serially homologous structures of the dentition in phylogenetic analyses. Overall, they provide long-overdue and clear empirical evidence that in-depth studies of patterns of integration constitute an essential step towards more realistic character construction and modeling. This approach is critical for more accurate morphological phylogenetics and, more generally, for testing macroevolutionary scenarios on groups of correlated characters.

opencc-zeroDec 2017View details →

Data from: R2s for correlated data: phylogenetic models, LMMs, and GLMMs

Many researchers want to report an R2 to measure the variance explained by a model. When the model includes correlation among data, such as phylogenetic models and mixed models, defining an R2 faces two conceptual problems. (i) It is unclear how to measure the variance explained by predictor (independent) variables when the model contains covariances. (ii) Researchers may want the R2 to include the variance explained by the covariances by asking questions such as "How much of the data is explained by phylogeny?" Here, I investigate three R2s for phylogenetic and mixed models. R2resid is an extension of the ordinary least-squares R2 that weights residuals by variances and covariances estimated by the model; it is closely related to R2glmm presented by Nakagawa and Schielzeth (2013). R2pred is based on predicting each residual from the fitted model and computing the variance between observed and predicted values. R2lik is based on the likelihood of fitted models and therefore reflects the amount of information that the models contain. These three R2s are formulated as partial R2s, making it possible to compare the contributions of predictor variables and variance components (phylogenetic signal and random effects) to the fit of models. Because partial R2s compare a full model with a reduced model without components of the full model, they are distinct from marginal R2s that partition additive components of the variance. The properties of the R2s for phylogenetic models were assessed using simulations for continuous and binary response data (phylogenetic generalized least squares and phylogenetic logistic regression). Because the R2s are designed broadly for any model for correlated data, the R2s were also compared for LMMs and GLMMs. R2resid, R2pred, and R2lik all have similar performance in describing the variance explained by different components of models. However, R2pred gives the most direct answer to the question of how much variance in the data is explained by a model. R2resid is most appropriate for comparing models fit to different datasets, because it does not depend on sample sizes. And R2lik is most appropriate to assess the importance of different components within the same model applied to the same data, because it is most closely associated with statistical significance tests.

opencc-zeroDec 2014View details →

Data from: Self-cannulation for haemodialysis: patient attributes, clinical correlates and self-cannulation predilection models

Background and objectives: With emerging evidence in support of home haemodialysis (HHD), patient factors which determine uptake of the modality need to be better understood. Self-cannulation (SC) is a major step towards enabling self-care 'in-centre' and home HD and remains the foremost barrier to its uptake. Human factors governing this aspect of HD practice are poorly understood. The aim of this study is to better understand self-cannulation preferences and factors which define them in end stage renal disease (ESRD). Design: In this multicentre study, 508 of 535 patients from predialysis (Group A: n=222), in-centre (Group B: n= 213), and home HD (Group C: n= 100) responded to a questionnaire with 3 self-cannulation questions. Simultaneously, data on clinical, cognitive and psychosocial variables were ascertained. The primary outcome measure was 'perceived ability to self-cannulate AV access'. Predictive models were developed using logistic regression analysis. Results: 36.6% of predialysis patients (A) and 29.1% of the 'in-centre' haemodialysis patients (B) felt able to consider SC for HD. Technical-skills related apprehension was highest in Group B (14.4%) patients. Response to routine venepuncture and the types of SC concerns were significant predictors of perceived ability to self-cannulate. There was no significant difference in concern for pain across the groups. In multivariable regression analysis, age, education level, 3MS score, hypoalbuminemia in Groups B & C and additionally, attitude to routine phlebotomy and the nature of specific concern for self-cannulation in Groups A, B and C, are significant predictors of SC preference. The unadjusted c-statistics of models 1 (derived from Group A and validated on A) and 2 (derived from B+C and validated on B), are 0.76(95% CI 0.69, 0.83) and 0.80 (95% CI 0.74, 0.87) respectively. Conclusions: There is high prevalence of perceived ability to self-cannulate. Modifiable SC concerns exist in ESRD. The use of predictive models to objectively define and target education and training strategies could potentially impact on HD self-management and future uptake of home HD.

opencc-zeroDec 2014View details →

Data from: Correlation between genetic diversity and environmental suitability: taking uncertainty from ecological niche models into account

The hindcast of shifts in the geographical ranges of species as estimated by ecological niche modelling (ENM) has been coupled with phylogeographical patterns, allowing the inference of past processes that drove population differentiation and genetic variability. However, more recently, some studies have suggested that maps of environmental suitability estimated by ENM may be correlated to species' abundance, raising the possibility of using environmental suitability to infer processes related to population demographic dynamics and genetic variability. In both cases, one of the main problems is that there is a wide variation in ENM development methods and climatic models. In this study, we analyse the relationship between heterozygosity (He) and environmental suitability from multiple ENMs for 25 population estimates for Dipteryx alata, a widely distributed, endemic tree species of the Cerrado region of central Brazil. We propose a new approach for generating a statistical distribution of correlations under randomly generated ENM. The confidence intervals from these distributions indicate how model selection with different properties affects the ability to detect a correlation of interest (e.g. the correlation between He and suitability). Additionally, our approach allows us to explore which particular ensemble of ENMs produces the better result for finding an association between environmental suitability and He. Caution is necessary when choosing a method or a climatic data set for modelling geographical distributions, but the new approach proposed here provides a conservative way to evaluate the ability of ensembles to detect patterns of interest.

openNov 2024View details →

Revealing nanoscale plasticity of metallic nanosponges with correlative and scale-bridging 3D microscopy and modelling

Data for manuscript "Revealing nanoscale plasticity of metallic nanosponges with correlative and scale-bridging 3D microscopy and modelling": SI Movies 01-12. Movies from Supporting Information. Description in file name.

opencc-by-4.0Jul 2023View details →

Data related to "Modeling the Diverse Effects of Divisive Normalization on Noise Correlations"

Data files for the paper, Modeling the Diverse Effects of Divisive Normalization on Noise Correlations, available on <a href="https://www.biorxiv.org/content/10.1101/2022.06.08.495145v3.abstract">bioRxiv</a> For the corresponding code toolbox, please see the <a href="https://github.com/oren-weiss/pairwiseRatioGaussians">Github repository</a> Please cite as:<blockquote>Modeling the Diverse Effects of Divisive Normalization on Noise CorrelationsOren Weiss, Hayley A. Bounds, Hillel Adesnik, Ruben Coen-CaglibioRxiv 2022.06.08.495145; doi: https://doi.org/10.1101/2022.06.08.495145</blockquote>

opencc-by-4.0Dec 2023View details →

Reproducible network changes occur in a mouse model of temporal lobe epilepsy but do not correlate with disease severity

Dataset for the publication: 'Reproducible network changes occur in a mouse model of temporal lobe epilepsy but do not correlate with disease severity ' Rigoni et al. 2023, Neurobiology of Disease, doi: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.nbd.2023.106382" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.nbd.2023.106382</a> Dataset description Data\data2publish\sub- : 50 epochs of raw epicranial EEG data (31 x 8001 x 50, channels x time x n_epochs, Fs=4k Hz). The epochs are available for 29 mice, on different sessions (ses-d0, ses-d28, ses-d29) depending on the animal  Data\data2publish\EA_info.xlsx: number of epileptiform activities automatically detected for each animal at d28 and d29 Data\data2publish\derivatives\eeg_preprocessing: results of the script A_EEG_preprocessing.m, for each animal and session Data\data2publish\derivatives\elec_layout: different layouts used to plot results. Mouse_layout_modif is the one used in Fig 4 Data\data2publish\derivatives\network_metrics_wpli: results of network analyses (script C_network_analyses.m) Data\data2publish\derivatives\wpli: connectivity matrices (30 x 30) obtained with the script B_connectivity_wpli.m for each animal, in each session, for each frequency band wit Code for analyses available here:  <a href="https://github.com/IsottaR/ir_mice_project_Zenodo">https://github.com/IsottaR/ir_mice_project_Zenodo </a> Abbreviations: EEG= electroencephalography

opencc-by-4.0Mar 2023View details →

JNK Activation Correlates with Cognitive Impairment and Alteration of the Post-Synaptic Element in the 5xFAD AD Mouse Model

The c-Jun N-terminal kinases (JNKs) are a family of proteins that, once activated by stress stimuli, can alter neuronal functions and survival. The JNK cascade plays a crucial role in the post-synaptic neuronal compartment by altering its structural organization and leading, at worst, to an overall impairment of neuronal communication. Increasing evidence suggests that synaptic impairment is the first neurodegenerative event in Alzheimer’s disease (AD). To better elucidate this mechanism, we longitudinally studied 5xFAD mice at three selected time points representative of human AD symptom progression. We tested the mice cognitive performance by using the radial arm water maze (RAWM) in parallel with biochemical evaluations of post-synaptic enriched protein fraction and total cortical parenchyma. We found that 5xFAD mice presented a strong JNK activation at 3.5 months of age in the post-synaptic enriched protein fraction. This JNK activation correlates with a structural alteration of the post-synaptic density area and with memory impairment at this early stage of the disease that progressively declines to cause cell death. These findings pave the way for future studies on JNK as a key player in early neurodegeneration and as an important therapeutic target for the development of new compounds able to tackle synaptic impairment in the early phase of AD pathology

opencc-by-4.0Jan 2022View details →

Data set for "Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit"

This data set is for the paper "Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit". It contains the raw DCA HD5 and DQMC plain text output files, as well as the scripts and final processed data used to generate figures 1-5 of the main text and supplementary figures 1-12. Copies of the figures and latex files are also included for completeness.

opencc-by-4.0Oct 2022View details →

Rank correlation results for the paper "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data"

This file contains the rank correlation results from the paper "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data".

opencc-by-4.0May 2024View details →

The ambient noise cross-correlation function and teleseismic events, the Love-wave phase velocities, Rayleigh-wave phase and group velocities and H/V, Vsv and Vsh model in the study region (CNCC)

The cross-correlation functions form EOBSArray (COR_CNCC), The Love-wave phase velocities (Love_phase), Rayleigh-wave phase (Rayleigh_phase) and group velocities (Rayleigh_group) and H/V (HtoV),and 3-D Vsv and Vsh model and related uncertainties (Vsv_Vsh_model) in the study region (CNCC) are archieved in the file named CNCC_data.7z.