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685 results for “errors”
Data from: Detecting macroevolutionary genotype-phenotype associations using error-corrected rates of protein convergence
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Data for: Gene tree estimation error with ultraconserved elements: An empirical study on Pseudapis bees
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Sources and types of errors in digital archaeological data
<p>Sources and types of errors in data collection and compilation, data processing and data usage that result in final global error, adapted and modified from Hunter and Beard 1992</p>
Dataset: Predictive error processing distinguishes between relevant and irrelevant errors after visuomotor learning
<p>Supplementary Data for <em><strong>Predictive error processing distinguishes between relevant and irrelevant errors after visuomotor learning</strong></em><em><strong> </strong></em>article</p> <p>Dataset associated with the following publication:</p> <p>Maurer, L. K., Joch, M., Hegele, M., Maurer, H. & Müller, H. (2019). Predictive error processing distinguishes between relevant and irrelevant errors after visuomotor learning. <em>Journal of Vision</em>, <em>19(4):18</em>, 1-13. https://doi.org/10.1167/19.4.18</p>
Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions"
<p>Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions" submitted to Water Resources Research.</p> <p>Contains:</p> <ul> <li>SWMM template files.</li> <li>Objective function values for all model runs.</li> <li>Jupyter Notebooks used to create figures and tables for the article.</li> <li>Copy of rainfall runoff data available from <a href="https://doi.org/10.5281/zenodo.3931582">https://doi.org/10.5281/zenodo.3931582</a></li> </ul> <p>For python implementations of the Hydrograph Matching Algorithm (Ewen 2011) see <a href="https://doi.org/10.5281/zenodo.3923792">https://doi.org/10.5281/zenodo.3923792</a></p> <p>Ewen, John. “Hydrograph Matching Method for Measuring Model Performance.” <em>Journal of Hydrology</em> 408, no. 1–2 (September 2011): 178–87. <a href="https://doi.org/10.1016/j.jhydrol.2011.07.038">https://doi.org/10.1016/j.jhydrol.2011.07.038</a>.</p>
Manuscript code & data: Foster et al. (2020) "Satellite-based monitoring of irrigation water use: assessing measurement errors and their implications for agricultural water management policy"
<p>Data to reproduce results presented in Foster, T., Mieno, T. and Brozovic, N. (2020). <em>Satellite-based monitoring of irrigation water use: assessing measurement errors and their implications for agricultural water management policy.</em> Water Resources Research. In Review. Files provide include:</p> <ul> <li>"ReviewMetadata_FosterWRR_2020.xlsx" - data needed to reproduce meta-analysis presented in the paper</li> <li>"MeasurementErrorCode_FosterWRR_2020.m" and "Foster2018_ProductionFunction.mat" - Matlab code and data needed to reproduce welfare loss analysis presented in the paper.</li> </ul>
Dataset for publication "Measurement of the Absolute Phase Error of Digitizers"
<p>This is the dataset related to the paper:</p> <p>G. Crotti, A. D. Femine, D. Gallo, D. Giordano, C. Landi and M. Luiso, "Measurement of the Absolute Phase Error of Digitizers," in <em>IEEE Transactions on Instrumentation and Measurement</em>, vol. 68, no. 6, pp. 1724-1731, June 2019.<br> doi: 10.1109/TIM.2018.2888919</p> <p>Excel file contains the data for Figures 2 and 3.</p>
Dataset for publication "Uncertainty Evaluation on the Absolute Phase Error of Digitizers"
<p>This is the dataset related to the paper</p> <p>Delle Femine, Antonio, Gallo, Daniele, Landi, Carmine, & Luiso, Mario. (2019). Uncertainty Evaluation on the Absolute Phase Error of Digitizers. Transactions of the Institute of Measurement and Control. http://doi.org/10.5281/zenodo.3600435</p> <p>that is identical to</p> <p>A. Delle Femine, D. Gallo, C. Landi, M. Luiso, “Uncertainty evaluation on the absolute phase error of digitizers”, Transactions of the Institute of Measurement and Control, Volume: 42 issue: 4, page(s): 749-758, 01 February 2020, doi: 10.1177/0142331219879836</p> <p> </p> <p> </p> <p>Excel file contains the data for Figures 6, 7, 8, 9.</p>
Data from: A critical appraisal of the placement of Xiphosura (Chelicerata) with account of known sources of phylogenetic error
Horseshoe crabs (Xiphosura) are traditionally regarded as sister to the clade of terrestrial chelicerates (Arachnida). This hypothesis has been challenged by recent phylogenomic analyses, but the non-monophyly of Arachnida has consistently been disregarded as artifactual. We reevaluated the placement of Xiphosura among chelicerates using the most complete phylogenetic dataset to date, expanding outgroup sampling and including data from whole genome sequencing projects. In spite of uncertainty in theplacement of some arachnid clades, all analyses show Xiphosura consistently nested within Arachnida as the sister group to Ricinulei (hooded tick spiders). It is apparent that the radiation of Arachnids is an old one and occurred over a brief period of time, resulting in several consecutive short internodes, and thus is a potential case for the confounding effects of incomplete lineage sorting (ILS). We simulated coalescent gene trees to explore the effects of increasing levels of ILS on the placement of horseshoe crabs. In addition, common sources of systematic error were evaluated, as well as the effects of fast evolving partitions and the dynamics of problematic long branch orders. Our results indicated that the placement of horseshoe crabs can not be explained by missing data, compositional biases, saturation, or incomplete lineage sorting. Interrogation of the phylogenetic signal showed that the majority of loci favor the derived placement of Xiphosura over a monophyletic Arachnida. Our analyses support the inference that horseshoe crabs represent a group of aquatic arachnids comparable to aquatic mites, breaking a long standing paradigm in chelicerate evolution and altering previous interpretations of the ancestral transition to the terrestrial habitat. Future studies testing chelicerate relationships should approach the task with a sampling strategy where the monophyly of Arachnida is not held as the premise.
Data from: Identifying and reducing AFLP genotyping error: an example of tradeoffs when comparing population structure in broadcast spawning versus brooding oysters
Phylogeographic inferences about gene flow are strengthened through comparison of co-distributed taxa, but also depend on adequate genomic sampling. Amplified Fragment Length Polymorphisms (AFLP) provide a rapid and inexpensive source of multilocus allele frequency data for making genomically robust inferences. Every AFLP study initially generates markers with a range of locus-specific genotyping error rates and applies criteria to select a subset for analysis. However, there has been very little empirical evaluation of the best tradeoff between culling all but the lowest-error loci to minimize overall genotyping error versus the potential for increasing population genetic signal by retaining more loci. Here, we used AFLPs to compare population structure in co-distributed broadcast spawning (Crassostrea virginica) and brooding (Ostrea equestris) oyster species. Using existing methods for almost entirely automated marker selection and scoring, genotyping error tradeoffs were evaluated by comparing results across a nested series of datasets with mean mismatch errors of 0, 1, 2, 3, 4 and >4%. Artifactual population structure was diagnosed in high-error datasets and we assessed the low-error point at which expected population substructure signal was lost. In both species we identified substructure patterns deemed to be inaccurate at error rates {less than or equal to}2% and >4%. In the species comparison, the optimum datasets showed higher gene flow for the brooding oyster with more oceanic salinity tolerances. AFLP tradeoffs may differ among studies, but our results suggest that important signal may be lost in the pursuit of 'acceptable' error levels and our procedures provide a general method for empirically exploring these tradeoffs.
Data from: Bayesian species delimitation can be robust to guide tree inference errors
The Bayesian method of species delimitation (Yang and Rannala, 2010) uses a so-called guide tree to reduce the number of models to be evaluated in the reversible-jump Markov chain Monte Carlo (rjMCMC) algorithm (Green, 1995). It has been pointed out that the method tends to over-split if a random population tree is used as the guide tree (Fujita and Leaché, 2011). Here we conduct a simulation study to examine the performance of the method under more realistic scenarios, that is, when the guide tree is inferred from the sequence data. We found that Bayesian species delimitation is in general robust to errors in the inferred guide tree.
Ordered phylogenomic subsampling enables diagnosis of systematic errors in the placement of the enigmatic arachnid order Palpigradi
<p><span><span><span><span><span><span><span><span><span><span><span>The miniaturized arachnid order Palpigradi has ambiguous phylogenetic affinities, due to its odd combination of plesiomorphic and derived morphological traits. This lineage has never been sampled in phylogenomic datasets because of its small body size and fragility of most species, a sampling gap of immediate concern to recent disputes over arachnid monophyly. To redress this gap, we sampled a population of the cave-inhabiting species <i>Eukoenenia spelaea</i> from Slovakia and inferred its placement in the phylogeny of Chelicerata using dense phylogenomic matrices of up to 1450 loci, drawn from high-quality transcriptomic libraries and complete genomes. The complete matrix included exemplars of all extant orders of Chelicerata. Analyses of the complete matrix recovered palpigrades as the sister group of the long-branch order Parasitiformes (ticks) with high support. However, sequential deletion of long-branch taxa revealed that the position of palpigrades is prone to topological instability. Phylogenomic subsampling approaches that maximized taxon or dataset completeness recovered palpigrades as the sister group of camel spiders (Solifugae), with modest support. While this relationship is congruent with the location and architecture of the coxal glands, a long-forgotten character system that opens in the pedipalpal segments only in palpigrades and solifuges, we show that nodal support values in concatenated supermatrices can mask high levels of underlying topological conflict in the placement of the enigmatic Palpigradi. </span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Interpreting the evolutionary regression: the interplay between observational and biological errors in phylogenetic comparative studies
Regressions of biological variables across species are rarely perfect. Usually there are residual deviations from the estimated model relationship, and such deviations commonly show a pattern of phylogenetic correlations indicating that they have biological causes. We discuss the origins and effects of phylogenetically correlated biological variation in regression studies. In particular, we discuss the interplay of biological deviations with deviations due to observational or measurement errors, which are also important in comparative studies based on estimated species means. We show how bias in estimated evolutionary regressions can arise from several sources, including phylogenetic inertia and either observational or biological error in the predictor variables. We show how all these biases can be estimated and corrected for in the presence of phylogenetic correlations. We present general formulas for incorporating measurement error in linear models with correlated data. We also show how alternative regression models, such as major-axis and reduced major-axis regression, which are often recommended when there is error in predictor variables, are strongly biased when there is biological variation in any part of the model. We argue that such methods should never be used to estimate evolutionary or allometric regression slopes.
Data from: The representation of prediction error in auditory cortex
To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of 'oddball' sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence.
Data from: SNP discovery in non-model organisms: strand-bias and base-substitution errors reduce conversion rates
Single nucleotide polymorphisms (SNPs) have become the marker of choice for genetic studies in organisms of conservation, commercial or biological interest. Most SNP discovery projects in nonmodel organisms apply a strategy for identifying putative SNPs based on filtering rules that account for random sequencing errors. Here, we analyse data used to develop 4723 novel SNPs for the commercially important deep-sea fish, orange roughy (Hoplostethus atlanticus), to assess the impact of not accounting for systematic sequencing errors when filtering identified polymorphisms when discovering SNPs. We used SAMtools to identify polymorphisms in a velvet assembly of genomic DNA sequence data from seven individuals. The resulting set of polymorphisms were filtered to minimize 'bycatch'—polymorphisms caused by sequencing or assembly error. An Illumina Infinium SNP chip was used to genotype a final set of 7714 polymorphisms across 1734 individuals. Five predictors were examined for their effect on the probability of obtaining an assayable SNP: depth of coverage, number of reads that support a variant, polymorphism type (e.g. A/C), strand-bias and Illumina SNP probe design score. Our results indicate that filtering out systematic sequencing errors could substantially improve the efficiency of SNP discovery. We show that BLASTX can be used as an efficient tool to identify single-copy genomic regions in the absence of a reference genome. The results have implications for research aiming to identify assayable SNPs and build SNP genotyping assays for nonmodel organisms.
Data from: Learning from the past: a reverberation of past errors in the cerebellar climbing fiber signal
The cerebellum allows us to rapidly adjust motor behavior to the needs of the situation. It is commonly assumed that cerebellum-based motor learning is guided by the difference between the desired and the actual behavior, i.e., by error information. Not only immediate but also future behavior will benefit from an error because it induces lasting changes of parallel fiber synapses on Purkinje cells (PCs), whose output mediates the behavioral adjustments. Olivary climbing fibers, likewise connecting with PCs, are thought to transport information on instant errors needed for the synaptic modification yet not to contribute to error memory. Here, we report work on monkeys tested in a saccadic learning paradigm that challenges this concept. We demonstrate not only a clear complex spikes (CS) signature of the error at the time of its occurrence but also a reverberation of this signature much later, before a new manifestation of the behavior, suitable to improve it.
Data from: A call for more transparent reporting of error rates: the quality of AFLP data in ecological and evolutionary research
Despite much discussion of the importance of quantifying and reporting genotyping error in molecular studies, it is still not standard practice in the literature. This is particularly a concern for amplified fragment length polymorphism (AFLP) studies, where differences in laboratory, peak-calling and locus-selection protocols can generate data sets varying widely in genotyping error rate, the number of loci used and potentially estimates of genetic diversity or differentiation. In our experience, papers rarely provide adequate information on AFLP reproducibility, making meaningful comparisons among studies difficult. To quantify the extent of this problem, we reviewed the current molecular ecology literature (470 recent AFLP articles) to determine the proportion of studies that report an error rate and follow established guidelines for assessing error. Fifty-four per cent of recent articles do not report any assessment of data set reproducibility. Of those studies that do claim to have assessed reproducibility, the majority (~90%) either do not report a specific error rate or do not provide sufficient details to allow the reader to judge whether error was assessed correctly. Even of the papers that do report an error rate and provide details, many (≥23%) do not follow recommended standards for quantifying error. These issues also exist for other marker types such as microsatellites, and next-generation sequencing techniques, particularly those which use restriction enzymes for fragment generation. Therefore, we urge all researchers conducting genotyping studies to estimate and more transparently report genotyping error using existing guidelines and encourage journals to enforce stricter standards for the publication of genotyping studies.
Data from: Inconsistent use of multiple comparison corrections in studies of population genetic structure: are some type I errors more tolerable than others?
Studies of genetic population structure often involve numerous tests of Hardy-Weinberg equilibrium (HWE), linkage disequilibrium (LD), and genetic differentiation. Tests of HWE or LD are important precursors to population structure assessments. When conducting multiple related statistical tests, type 1 error increases, e.g., familywise error rate (FWER) inflation. FWER inflation can alter the results of statistical tests and thus the conclusions. Authors are aware of the need to control for FWER inflation, but there has been low consistency of use. Furthermore, there is a potential for the choice of correction methods to be exploited to selectively use FWER corrections to avoid data exclusion or to result in increased the rejection of null hypotheses. We surveyed literature from 2011-2013 to determine if studies of population structure assess LD and HWE and if FWER corrections were applied consistently across different types of genetic differentiation, linkage disequilibrium, and Hardy-Weinberg equilibrium tests. We found a lack of documentation of FWER corrections in studies, and we advocate for authors to be more cognizant in reporting their corrections. We also found significantly inconsistent FWER corrections, with a bias towards less restrictive correction on genetic differentiation and more restrictive corrections with LD and HWE. While varied adjustments of FWER for different types of analyses might be justified, papers with inconsistent usage across tests of HWE, LD and genetic differentiation did not present rationale for their FWER corrections. We also found a lack of documentation of HWE, LD and FWER corrections in studies. We encourage authors to report statistical tests and related FWER corrections, use FWER corrections consistently or justify their different methods in the same study.
Data from: Trial-and-error copying of demonstrated actions reveals how fledglings learn to 'imitate' their mothers
Understanding how humans and other animals learn to perform an act from seeing it done has been a major challenge in the study of social learning. To determine whether this ability is based on 'true imitation', many studies have applied the two-action experimental paradigm, examining whether subjects learn to perform the specific action demonstrated to them. Here, we show that the insights gained from animals' success in two-action experiments may be limited, and that a better understanding is achieved by monitoring subjects' entire behavioural repertoire. Hand-reared house sparrows that followed a model of a mother demonstrator were successful in learning to find seeds hidden under a leaf, using the action demonstrated by the mother (either pushing the leaf or pecking it). However, they also produced behaviours that had not been demonstrated but were nevertheless related to the demonstrated act. This finding suggests that while the learners were clearly influenced by the demonstrator, they did not accurately imitate her. Rather, they used their own behavioural repertoire, gradually fitting it to the demonstrated task solution through trial and error. This process is consistent with recent views on how animals learn to imitate, and may contribute to a unified process-level analysis of social learning mechanisms.
Data from: Two sources of bias explain errors in facial age estimation
Accurate age estimates underpin our everyday social interactions, the provision of age-restricted services and police investigations. Previous work suggests that these judgments are error-prone, but the processes giving rise to these errors are not understood. Here we present the first systematic test of bias in age estimation using a large database of standardized passport images of heterogeneous ages (n = 3948). In three experiments we tested a range of perceiver age groups (n = 84), and found average age estimation error to be approximately 8 years. We show that this error can be attributed to two separable sources of bias. First, and accounting for the vast majority of variance, our results show an assimilative serial dependency whereby estimates are systematically biased towards the age of the preceding face. Second, younger faces are generally perceived to be older than they are, and older faces to be younger. In combination, these biases account for around 95% of variance in age estimates. We conclude that that perception of age is modulated by representations that encode both a viewer's recent and normative exposure to faces. The finding that age perception is subject to strong top-down influences based on our immediate experience has implications for our understanding of perceptual processes involved in face perception, and for improving accuracy of age estimation in important real world tasks.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.