Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
184
datasets available to search
ShareScore release 0.9.0
Dataset results
184 results for “variability analysis”
FIGURE 9 in Taxonomic revision of Cypridopsis silvestrii comb. nov. (Ostracoda, Crustacea) from Patagonia, Argentina with morphometric analysis of their intraspecific shape variability and sexual dimorphism
FIGURE 9. Boxplots showing carapace length (a), Height (b) and H:L (c) of ETf, ETm, ETC, and ES populations. The line within the box marks the median; the lower and upper boundaries of the box indicate the 25th and 75th percentiles, respectively. Error bars above and below the box indicate the 90th and 10th percentiles, respectively, and black points indicate outliers.
FIGURE 6 in Taxonomic revision of Cypridopsis silvestrii comb. nov. (Ostracoda, Crustacea) from Patagonia, Argentina with morphometric analysis of their intraspecific shape variability and sexual dimorphism
FIGURE 6. Nonmetric Multidimensional Scaling (n-MDS) plot showing shape variability (valve outlines were normalized for area) of extant and subfossil populations, with superimposition of reconstructed mean shape outline of each population.
Data and analysis for "Fldgen v1.0: An Emulator with Internal Variability and Space-Time Correlation for Earth System Models"
<p>This is an archive of the raw data and analysis source code for the paper "Fldgen v1.0: An Emulator with Internal Variability and Space-Time Correlation for Earth System Models". The archive contains:</p> <ul> <li><strong>devel.Rmd : </strong>Source code for the worksheet that contains the early development and figures for the paper.</li> <li><strong>devel.html</strong> : HTML rendering of devel.Rmd</li> <li><strong>lg-ensemble-stats.Rmd </strong>: Source code for the worksheet that contains the statistical analysis described in the paper.</li> <li><strong>lg-ensemble-stats.html</strong> : HTML rendering of lg-ensemble-stats.Rmd</li> <li><strong>cc-analysis.Rmd </strong>: Analysis of the compromise conjecture raised by some readers of the paper</li> <li><strong>cc-analysis.nb.html</strong> : HTML rendering of cc-analysis.Rmd</li> <li><strong>data.tar.bz2 </strong>: Input data for the analyses above.</li> </ul> <p>The source code in this archive is written in R and requires the R runtime environment. It also uses the fldgen package, version 1.0.0, which is available at <a href="https://github.com/JGCRI/fldgen">https://github.com/JGCRI/fldgen</a></p> <p> </p>
FIGURE 5. Principal components analysis depicting morphometric variables distinguishing northern subspecies, H. l in Phylogenetic structure of Holbrookia lacerata (Cope 1880) (Squamata: Phrynosomatidae): one species or two?
FIGURE 5. Principal components analysis depicting morphometric variables distinguishing northern subspecies, H. l. lacerata (green), from southern subspecies, H. l. subcaudalis (purple).
Fig. 4 in Several Subspecies or Phenotypic Plasticity? A Geometric Morphometric and Molecular Analysis of Variability of the Mayan Cichlid Mayaheros urophthalmus in the Yucatan
Fig. 4. Axis of CVA under aquatic environment approach with ellipses of the probability of 95%, and the grid of morphometric space of CVA with a factor of deformation ¼ 0.1; (A) axis 1 of CVA and (B) axis 2 of CVA.
Fig. 3. CVA 1 in Several Subspecies or Phenotypic Plasticity? A Geometric Morphometric and Molecular Analysis of Variability of the Mayan Cichlid Mayaheros urophthalmus in the Yucatan
Fig. 3. CVA 1 vs. CVA 2 by population at geometric morphometric space delimited by minimum convex polygons, and the grid of morphometric space of CVA with a factor of deformation ¼ 0.1; (A) axis 1 of CVA and (B) axis 2 of CVA.
Fig. 1 in Several Subspecies or Phenotypic Plasticity? A Geometric Morphometric and Molecular Analysis of Variability of the Mayan Cichlid Mayaheros urophthalmus in the Yucatan
Fig. 1. Study area, Yucatan Peninsula. Localities of M. urophthalmus taken into account for the geometric morphometric analysis, in gray numbers. Localities with genetic data, marked with an asterisk. Localities from nominal species included in the morphometric analysis: M. alborus (15), M. cienagae (10), M. conchitae (8), M. mayorum (6), and M. zebra (9).
Fig. 2 in Several Subspecies or Phenotypic Plasticity? A Geometric Morphometric and Molecular Analysis of Variability of the Mayan Cichlid Mayaheros urophthalmus in the Yucatan
Fig. 2. Constellation of landmarks and semilandmarks for the geometric morphometric analysis showing Procrustes superimposition of landmarks and semilandmarks. Anatomical positions of landmarks: Landmark 1—intersection between the posterior base of dorsal fin and caudal peduncle; Landmark 2—the most distal pore of the end of lateral line; Landmark 3—intersection between the posterior base of the pelvic fin and caudal peduncle; Landmark 4—intersection between anterior base of pelvic fin and belly; Landmark 5—apical intersection between subopercle and interopercle; Landmark 6—commissure of dentary at the more posterior end at its junction with the anguloarticular, quadrates, and ectometapterygoid bone; Landmarks 7 and 8—delimitation of the width of the commissure of dentary at its junction with the maxilla; Landmarks 9 and 10—delimitation of the width of the dentary at the more anterior end; Landmarks 10 and 12—delimitation of the width of the premaxilla at the more anterior end; Landmark 11—dorsal end of edge between opercle and cheek; Landmarks 12 to 24—the curve of 13 semilandmarks beginning at the intersection between the premaxilla and ascending process at semilandmark 12, the curve traced upwards until the base of dorsal fin at semilandmark 24.
Meta-analysis of scRNA-seq Co-expression in Human Neural Organoids Reveals High Variability in Recapitulating Primary Tissue
<p>Contains all code and data for Werner and Gillis, Meta-analysis of scRNA-seq Co-expression in Human Neural Organoids Reveals High Variability in Recapitulating Primary Tissue, 2024. </p> <p>Additionally, the code and data for this paper can be found at https://github.com/JonathanMWerner/meta_organoid_analysis with an easy to view github markdown file containing all the code used to generate all figure panel plots at https://github.com/JonathanMWerner/meta_organoid_analysis/blob/main/figure_plots_with_data_code.md.</p> <p>Due to file size limits on github, there are several data files not available on github, but are available here on zenodo in the data_for_plots.zip file, see below:</p> <pre>umap_embeddings_Fig2A.Rdata<br>cross_dataset_aggregated_exp_metaMarker_all_fetal_SuppFig1B_Fig2E.Rdata<br>organoid_egad_results_ranked_6_26_24_Fig3D.Rdata<br>fetal_egad_results_ranked_6_26_24_Fig3D.Rdata<br>org_eigenvec_matrices_SuppFig3CD.Rdata</pre> <p><br>The R package developed for this paper is available at https://github.com/JonathanMWerner/preservedCoexp</p>
Figure 5 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 5. Scatterplot of the relationship of PC1 on body weight separated by group (a), on body weight separated by sex (b), OvWBW (c) and NgWBW (d) for females separated by group.
Figure 3 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 3. Schematic representation of the series of growth increments (GINC) read over the dorsal surface of the gladius, the filtering process and the back-calculation of the gladius growth.
Figure 1 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 1. Spatial representation of the study area. (a–c) Positions of the samples of Illex argentinus collected from trawlers south-southeast of Brazil between 22° and 33°S and 45 and 722 m depth from 2001 to 2013. (b) Samples used in geometric morphometric analysis. (c) Samples used in traditional morphometric analysis. (d) Samples collected during a research cruise during August of 2004 in the same area to identify size-selective processes. Lines in maps represent 100, 300 and 700 m depth.
Figure 4 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 4. Length distributions of the (a) Local Group (LG) and the (b) Migratory Group (MG) captured south-southeast of Brazil between 2009 and 2013. Scatterplots of the first (PC1) and second (PC2) components of the principal component analysis using body landmarks separated by group (c) and by sex (d). Scatterplot of relationship of PC1 on centroid size separated by group (e) and by sex (f).
Figure 2 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 2. Landmark configuration on the body of Illex argentinus. Dashed line represents the longitudinal axis of the body.
Figure 8 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 8. Length distributions of Illex argentinus captured in south-southeastern Brazil between 22° and 33°S and 45 and 722 m depth from 2001 to 2013.
Figure 7 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 7. (a) Mean gladius length (GL) in research cruise, and (b) mean individuals recent growth trajectories of squid captured in research cruise reconstructed from gladius.
Figure 10 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 10. Size differentiation of squid groups during the period of growth reconstructed expressed by the variation of the coefficient of asymmetry (g1) of the length frequency distributions by growth interval (days).
Figure 9 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 9. Gladius length frequency distributions of Illex argentinus reconstructed for the last 15 days before the capture from the measured increments on the gladius for the trawls 2–4 (T2-4) and trawls 9–14 (T9-14) of the research cruise.
Figure 6 in Analysis of shape variability and life history strategies of Illex argentinus in the northern extreme of species distribution as a tool to differentiate spawning groups
Figure 6. Barplots represents the length distributions of males and females of Illex argentinus captured during the fourth trimester of 2006 south-southeast of Brazil and a sample from the Uruguayan/Argentine common fishing zone collected in 2005, here defined as pre-migratory group (J). The analysis aimed to verify a possible correspondence between J and the expected MG, represented by two samples collected in the south (S) and central (C) portions of the studied area and if J is morphometrically different from the LG, captured in the north (N) portion of study area (Figure 1(c)). Plots represent the principal component analysis of the samples N, C, S and J. FRAL, length of the fourth right arm; BW, body weight; MW, mantle weight; MP, mantle perimeter.
FIGURE. DnaSP DNA polymorphism analysis - Nucleotide variability (Pi) comparison between Strobilanthes lupulina and S. glandulata. The window length and step size were set to 600bp and 200bp respectively. The most varying regions and the commonly used barcoding regions are listed against the base-pair differences found. in Strobilanthes glandulata (Acanthaceae), a new species from Sri Lanka based on the morphological and molecular evidences
FIGURE. DnaSP DNA polymorphism analysis - Nucleotide variability (Pi) comparison between Strobilanthes lupulina and S. glandulata. The window length and step size were set to 600bp and 200bp respectively. The most varying regions and the commonly used barcoding regions are listed against the base-pair differences found.
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.