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30 results for “population clustering”
The effect of dynamical states on galaxy clusters populations. I. Classification of dynamical states
<p>This repository contains three figures mentioned in "The effect of dynamical states on galaxy clusters populations. I. Classification of dynamical states" <em>(DOI to follow on publication)</em>.</p> <p>We show the contours of the X-ray surface brightness distribution (solid green lines) and the distribution of galaxies belonging to the red sequence (solid gray lines). Black crosses symbolize the positions of the X-ray peaks, black "X" marks represent the positions of the X-ray centroids, and open red circles denote the positions of the BCGs. The blue circle corresponds to the R200 of each cluster.</p>
Magellan/M2FS Spectroscopy of Galaxy Clusters: Stellar Population Model and Application to Abell 267
<p>supplementary data products, including all sky-subtracted spectra from individual galaxies, as well as random draws from posterior PDFs for model parameters (see included README file)</p>
Data for Survival probabilities of atmospheric particles: comparison based on theory, cluster population simulations, and observations in Beijing
<p>Data for<em> Survival probabilities of atmospheric particles: comparison based on theory, cluster population simulations, and observations in Beijing </em>(https://doi.org/10.5194/acp-2022-484)</p> <p>Contact Santeri Tuovinen (santeri.tuovinen@helsinki.fi) for more details.</p>
Galaxy populations in the Hydra I cluster from the VEGAS survey III. The realm of low-surface brightness features and intra-cluster light
<p><span>This appendix provides the azimuthally-averaged surface bright</span><span>ness and colour profiles of the sample galaxies listed in Table 1 of the paper "Galaxy populations in the Hydra I cluster from the VEGAS survey III. The realm of low-surface brightness features and intra-cluster light", by <span>Marilena Spavone</span><span>,</span><span> Enrichetta Iodice</span><span>,</span><span> Felipe S. Lohmann</span><span>, Magda Arnaboldi</span><span>, Michael Hilker</span><span>, Antonio La </span><span>Marca</span><span>, Rosa Calvi</span><span>, Michele Cantiello</span><span>, Enrico M. Corsini</span><span>, Giuseppe D’Ago</span><span>, Duncan A. Forbes</span><span>, Marco </span><span>Mirabile</span><span>, and Marina Rejkuba.</span><br></span></p>
On the Observability of Individual Population III Stars and Their Stellar-mass Black Hole Accretion Disks through Cluster Caustic Transits
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018ApJS..234...41W/abstract">On the Observability of Individual Population III Stars and Their Stellar-mass Black Hole Accretion Disks through Cluster Caustic Transits</a></p>
Pairwise distance demarcation of species in the family Coronaviridae. a, Diagonal matrix of PPDs of 2,505 viruses clustered according to 49 coronavirus species, 39 established and 10 pending or tentative, and ordered from the most to least populous species, from left to right; green and white, PPDs smaller and larger than the inter-species threshold, respectively. Areas of the green squares along the diagonal are proportional to the virus sampling of the respective species, and virus prototypes of the five most sampled species are specified to the left; asterisks indicate species that include viruses whose intra-species PPDs crossed the inter-species threshold (threshold 'violators'). b, Maximal intra-species PPDs (x axis, linear scale) plotted against virus sampling (y axis, log scale) for 49 species (green dots) of the Coronaviridae. Indicated are the acronyms of virus prototypes of the seven most sampled species. Green and blue plot sections represent intra-species and intra-subgenera PPD ranges. The vertical black line indicates the inter-species threshold. c, Shown are the PDs of non-identical residues (y axis) for four viruses representing three major phylogenetic lineages (clades) of the species Severe acute respiratorysyndrome-related coronavirus (panel b) and all pairs of the 256 viruses of this species ('all pairs'). The PD values were derived from pairwise distances in the MSA that were calculated using an identity matrix. Panels a and b were adopted from the DEmARC v.1.4 output. in The species Severe acute respiratory syndromerelated coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2
Pairwise distance demarcation of species in the family Coronaviridae. a, Diagonal matrix of PPDs of 2,505 viruses clustered according to 49 coronavirus species, 39 established and 10 pending or tentative, and ordered from the most to least populous species, from left to right; green and white, PPDs smaller and larger than the inter-species threshold, respectively. Areas of the green squares along the diagonal are proportional to the virus sampling of the respective species, and virus prototypes of the five most sampled species are specified to the left; asterisks indicate species that include viruses whose intra-species PPDs crossed the inter-species threshold (threshold 'violators'). b, Maximal intra-species PPDs (x axis, linear scale) plotted against virus sampling (y axis, log scale) for 49 species (green dots) of the Coronaviridae. Indicated are the acronyms of virus prototypes of the seven most sampled species. Green and blue plot sections represent intra-species and intra-subgenera PPD ranges. The vertical black line indicates the inter-species threshold. c, Shown are the PDs of non-identical residues (y axis) for four viruses representing three major phylogenetic lineages (clades) of the species Severe acute respiratorysyndrome-related coronavirus (panel b) and all pairs of the 256 viruses of this species ('all pairs'). The PD values were derived from pairwise distances in the MSA that were calculated using an identity matrix. Panels a and b were adopted from the DEmARC v.1.4 output.
Data from: Population genomic analyses reveal a highly differentiated and endangered genetic cluster of northern goshawks (Accipiter gentilis laingi) in Haida Gwaii
Accurate knowledge of geographic ranges and genetic relationships among populations is important when managing a species or population of conservation concern. Along the western coast of Canada, a subspecies of the northern goshawk (Accipiter gentilis laingi) is legally designated as Threatened. The range and distinctness of this form, in comparison to the broadly distributed North American subspecies (Accipiter gentilis atricapillus), is unclear. Given this morphological uncertainty, we analyzed genomic relationships in thousands of single nucleotide polymorphisms identified using genotyping-by-sequencing of high-quality genetic samples. Results revealed a genetically distinct population of northern goshawks on the archipelago of Haida Gwaii and subtle structuring among other North American sampling regions. We then developed genotyping assays for ten loci that are highly differentiated between the two main genetic clusters, allowing inclusion of hundreds of low-quality samples and confirming that the distinct genetic cluster is restricted to Haida Gwaii. As the laingi form was originally described as being based in Haida Gwaii (where the type specimen is from), further morphological analysis may result in this name being restricted to the Haida Gwaii genetic cluster. Regardless of taxonomic treatment, the distinct Haida Gwaii genetic cluster along with the small and declining population size of the Haida Gwaii population suggests a high risk of extinction of an ecologically and genetically distinct form of northern goshawk. Outside of Haida Gwaii, sampling regions along the coast of BC and southeast Alaska (often considered regions inhabited by laingi) show some subtle differentiation from other North American regions. These results will increase the effectiveness of conservation management of northern goshawks in northwestern North America. More broadly, other conservation-related studies of genetic variation may benefit from the two-step approach we employed that first surveys genomic variation using high-quality samples and then genotypes low-quality samples at particularly informative loci.
Data from: Genetic evidence of female kin clusters in a continuous population of a solitary carnivore, the Eurasian lynx
Large terrestrial carnivores can sometimes display strong family bonds affecting the spatial distribution of related individuals. We studied the spatial genetic relatedness and family structure of female Eurasian lynx, continuously distributed in southern Finland. We hypothesized that closely related females form matrilineal assemblages, clustering together with relatives living in the neighboring areas. We evaluated this hypothesis using tissue samples of 133 legally harvested female lynx (from year 2007 to 2015), genotyped with 23 microsatellite markers, and tested for possible spatial genetic family structure using a combination of Bayesian clustering, spatial autocorrelation, and forensic genetic parentage analysis. The study population had three potential family genetic clusters, with a high degree of admixture and geographic overlap, and showed a weak but significant negative relationship between pairwise genetic and geographic distance. Moreover, parentage analysis indicated that 64% of the females had one or more close relatives (sister, mother, or daughter) within the study population. Individuals identified as close kin consistently assigned to the same putative family genetic cluster. They also were sampled closer geographically than females on average, although variation was large. Our results support the possibility that Eurasian lynx forms matrilineal assemblages, and comparisons with males are now required to further assess this hypothesis.
Data from: Population clustering and clonal structure evidence the relict state of Ulmus minor Mill. in the Balearic Islands
Field elm (Ulmus minor) is a riparian tree that grows in rare, small populations scattered along temporary watercourses in the Balearic Islands, nowadays mostly covered with Mediterranean vegetation. Agriculture and farming on the fertile land along the periodically flooded plains have reduced the elm populations to sparse tree lines along the creek beds. The presence of field elm in this very anthropic landscape has led some authors to consider it as an introduced species in the Balearics. However, pollen data suggest these elms may be the remains of larger populations experiencing continuous population shrinkage during the Holocene, and hence be native to the isles. In this paper, we apply genetic markers to assess whether field elm is or is not indigenous to the Balearic Islands. We compare the genetic variation in nine nuclear microsatellites of six Balearic populations (three in each of the largest islands, Majorca and Minorca) with that of three natural Iberian populations located in two regions, one geologically (Baetic mountains, SE Iberia) and another historically (Catalonia, NE Iberia) related to the islands. Principal coordinates analysis and Bayesian clustering methods reveal a strong genetic differentiation of the Balearic populations from the Iberian ones, and even among islands, which support their native origin. Genotypic variation in the islands is very low and clonal reproduction is very high compared with the mainland, as it is frequently observed in populations of clonal species where sexual reproduction is limited. We discuss the practical implications of these findings for the conservation of elm genetic resources of these findings.
Data from: Phylogeography of var gene repertoires reveals fine-scale geospatial clustering of Plasmodium falciparum populations in a highly endemic area
Plasmodium falciparum malaria is a major global health problem that is being targeted for progressive elimination. Knowledge of local disease transmission patterns in endemic countries is critical to these elimination efforts. To investigate fine-scale patterns of malaria transmission, we have compared repertoires of rapidly evolving var genes in a highly endemic area. A total of 3680 high quality DBLα sequences were obtained from 68 P. falciparum isolates from ten villages spread over two distinct catchment areas on the north coast of Papua New Guinea (PNG). Modeling of the extent of var gene diversity in the two parasite populations predicts more than twice as many var gene alleles circulating within each catchment (Mugil=906; Wosera=1094) than previously recognized in PNG (Amele=369). In addition, there were limited levels of var gene sharing between populations, consistent with local parasite population structure. Phylogeographic analyses demonstrate that while neutrally evolving microsatellite markers identified population structure only at the catchment level, var gene repertoires reveal further fine-scale geospatial clustering of parasite isolates. The clustering of parasite isolates by village in Mugil, but not in Wosera was consistent with the physical and cultural isolation of the human populations in the two catchments. The study highlights the micro-heterogeneity of P. falciparum transmission in highly endemic areas and demonstrates the potential of var genes as markers of local patterns of parasite population structure.
Efficacy of a Multi-faceted Intervention to Deprescribe Proton Pump Inhibitors (PPI) in Primary Care: a Population-based, Pragmatic, Cluster-randomized Controlled Trial.
ClinicalTrials.gov study NCT04255823. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Population genomic analyses reveal a highly differentiated and endangered genetic cluster of northern goshawks (Accipiter gentilis laingi) in Haida Gwaii
Open the record for dataset details and reuse information.
Data from: Genetic evidence of female kin clusters in a continuous population of a solitary carnivore, the Eurasian lynx
Open the record for dataset details and reuse information.
Data from: Population clustering and clonal structure evidence the relict state of Ulmus minor Mill. in the Balearic Islands
Open the record for dataset details and reuse information.
Data from: Phylogeography of var gene repertoires reveals fine-scale geospatial clustering of Plasmodium falciparum populations in a highly endemic area
Open the record for dataset details and reuse information.
Data from: Islands and streams: clusters and gene flow in wild barley populations from the Levant
The domestication of plants frequently results in a high level of genetic differentiation between domesticated plants and their wild progenitors. This process is counteracted by gene flow between wild and domesticated plants because they are usually able to inter-mate and to exchange genes. We investigated the extent of gene flow between wild barley Hordeum spontaneum and cultivated barley Hordeum vulgare, and its effect on population structure in wild barley by analyzing a collection of 896 wild barley accessions (Barley1K) from Israel and all available Israeli H. vulgare accessions from the Israeli gene bank. We compared the performance of simple sequence repeats (SSR) and single nucleotide polymorphisms (SNP) marker data genotyped over a core collection in estimating population parameters. Estimates of gene flow rates with SSR markers indicated a high level of introgression from cultivated barley into wild barley. After removing accessions from the wild barley sample that were recently admixed with cultivated barley, the inference of population structure improved significantly. Both SSR and SNP markers showed that the genetic population structure of wild barley in Israel corresponds to the three major ecogeographic regions: the coast, the Mediterranean north, and the deserts in the Jordan valley and the South. Gene flow rates were estimated to be higher from north to south than in the opposite direction. As has been observed in other crop species, there is a significant exchange of alleles between the wild species and domesticated varieties that needs to be accounted for in the population genetic analysis of domestication.
Data from: Estimating density from presence/absence data in clustered populations
<p>1. Inventories of plant populations are fundamental in ecological research and monitoring, but such surveys are often prone to field assessment errors. Presence/absence (P/A) sampling may have advantages over plant cover assessments for reducing such errors. However, the linking between P/A data and plant density depends on model assumptions for plant spatial distributions. Previous studies have shown, for example, how that plant density can be estimated under Poisson model assumptions on the plant locations. In this study new methods are developed and evaluated for linking P/A data with plant density assuming that plants occur in clustered spatial patterns.<br> 2. New theory was derived for estimating plant density under Neyman-Scott type cluster models such as the Matérn and Thomas cluster processes. Suggested estimators, corresponding confidence intervals, and a proposed goodness-of-fit test were evaluated in a Monte-Carlo simulation study assuming a Matérn cluster process. Further, the estimators were applied to plant data from environmental monitoring in Sweden to demonstrate their empirical application.<br> 3. The simulation study showed that our methods work well for large enough sample sizes. The judgment of what is "large enough'' is often difficult, but simulations indicate that a sample size is large enough when the sampling distributions of the parameter estimators are symmetric or mildly skewed. Bootstrap may be used to check whether this is true. The empirical results suggests that the derived methodology may be useful for estimating density of plants such as <em>Leucanthemum vulgare</em> and <em>Scorzonera humilis</em>.<br> 4. By developing estimators of plant density from P/A data under realistic model assumptions about plants' spatial distributions, P/A sampling will become a more useful tool for inventories of plant populations. Our new theory is an important step in this direction.</p>
Data from: STRUCTURE is more robust than other clustering methods in simulated mixed-ploidy populations
Analyses of population genetic structure has become a standard approach in population genetics. In polyploid complexes, clustering analyses can elucidate the origin of polyploid populations and patterns of admixture between different cytotypes. However, combining diploid and polyploid data can theoretically lead to biased inference with (artefactual) clustering by ploidy. We used simulated mixed-ploidy (diploid-autotetraploid) data to systematically compare the performance of k-means clustering and the model-based clustering methods implemented in STRUCTURE, ADMIXTURE, FASTSTRUCTURE and INSTRUCT under different scenarios of differentiation and with different marker types. Under scenarios of strong population differentiation, the tested applications performed equally well. However, when population differentiation was weak, STRUCTURE was the only method that allowed unbiased inference with markers with limited genotypic information (co-dominant markers with unknown do sage or dominant markers). Still, since STRUCTURE was comparably slow the much faster but less powerful FASTSTRUCTURE provides a reasonable alternative for large datasets. Finally, although bias makes k-means clustering unsuitable for markers with incomplete genotype information, given large numbers of loci (>1000) with known dosage k-means clustering was superior to FASTSTRUCTURE in terms of power and speed. We conclude that STRUCTURE is the most robust method for the analysis of genetic structure in mixed-ploidy populations, although alternative methods should be considered under some specific conditions.
Data from: The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis
The inference of population genetic structures is essential in many research areas in population genetics, conservation biology and evolutionary biology. Recently, unsupervised Bayesian clustering algorithms have been developed to detect a hidden population structure from genotypic data, assuming among others that individuals taken from the population are unrelated. Because of this hypothesis, markers in a sample taken from a subpopulation can be considered to be in Hardy-Weinberg and linkage equilibrium. However, close relatives might be sampled from the same subpopulation, and consequently, might cause Hardy-Weinberg and linkage disequilibrium and thus bias a population genetic structure analysis. In this study, we used simulated and real data to investigate the impact of close relatives in a sample on Bayesian population structure analysis. We also showed that, when close relatives were identified by a pedigree reconstruction approach and removed, the accuracy of a population genetic structure analysis can be greatly improved. The results indicate that unsupervised Bayesian clustering algorithms cannot be used blindly to detect genetic structure in a sample with closely related individuals. Rather, when closely related individuals are suspected to be frequent in a sample, these individuals should be first identified and removed before conducting a population structure analysis.
The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical datasets
<p class="CxSpFirst">The software program STRUCTURE is one of the most cited tools for determining population structure. To infer the optimal number of clusters from STRUCTURE output, the Δ<i>K</i> method is often applied. However, a recent study relying on simulated microsatellite data suggested that this method has a downward bias in its estimation of <i>K</i> and is sensitive to uneven sampling. If this finding holds for empirical datasets, conclusions about the scale of gene flow may have to be revised for a large number of studies. To determine the impact of method choice, we applied recently described estimators of <i>K</i> to re-estimate genetic structure in 41 empirical microsatellite datasets; 15 from a broad range of taxa and 26 focused on a diverse phylogenetic group, coral. We compared alternative estimates of <i>K</i> (Puechmaille statistics) with traditional (Δ<i>K</i> and posterior probability) estimates and found widespread disagreement of estimators across datasets. Thus, one estimator alone is insufficient for determining the optimal number of clusters regardless of study organism or evenness of sampling scheme. Subsequent analysis of molecular variance (AMOVA) between clustering solutions did not necessarily clarify which solution was best. To better infer population structure, we suggest a combination of visual inspection of STRUCTURE plots and calculation of the alternative estimators at various thresholds in addition to Δ<i>K</i>. Differences between estimators could reveal patterns with important biological implications, such as the potential for more population structure than previously estimated, as was the case for many studies reanalyzed here.</p>
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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.