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.
1,297
datasets available to search
ShareScore release 0.9.0
Dataset results
1,297 results for “differential analysis”
Datasets for : High-resolution detection and differential expression analysis of transcription start sites using MAPCap
<p>This dataset corresponds to the study: High-resolution detection and differential expression analysis of transcription start sites using MAPCap (Bhardwaj et. al. 2018)</p> <p>It includes:</p> <p> - TSS identified using MAPCap in stage 15 embryos and larvae.</p> <p> - Differentially expressed TSS using MAPCap (FDR < 0.05) in larvae.</p> <p> - Common and stage-specific enhancer TSS identified in this study</p>
Fig. 5 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 5 Differential transcript expression analysis. Bar charts represent the enriched molecular functions associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Fig. 4 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 4 Differential transcript expression analysis. Bar charts represent the enriched biological processes associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Fig. 2 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 2 Scheme of the methodology employed in this study. In a first approach, the reference transcriptome (workflow in grey) was assembled de novo from three distinct life cycle stages: the feeding stage alone (asexual generation; note that in young feeding stages, the buccal funnel is located inside in the trunk), the feeding stage with Prometheus larva(e) attached to its trunk (sexual generation) and the free-swimming chordoid larva. Secondly, in the differential gene expression analysis (workflow in black), only two different conditions were investigated: feeding stages with Prometheus larva(e) attached to its trunk and feeding stages alone. Finally, sequenced reads were mapped to the reference transcriptome
Fig. 6 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 6 Differential transcript expression analysis. Bar charts represent the enriched cellular components associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Fig. 1 in Multilocus population analysis of Gavia immer (Aves: Gaviidae) mtDNA reveals low genetic diversity and lack of differentiation across the species breeding range
Fig. 1 Haplotype network constructed using the median joining method. Haplotype numbers are indicated. Circle patterns represent coastal sampling locations: GZ Galicia, Spain, MX Mexico, GE Germany, NJ New Jersey, US, MI Michigan, US, CA Canada, FL Florida, US. Circle surfaces are roughly proportional to the number of individuals with each haplotype (Table 3)
Protocol for Genome-scale differential flux analysis (GS-FFA)
<p><span>Here, we introduce a genome-scale differential flux analysis (GS-DFA) protocol to interrogate the metabolic variances derived from condition-specific gene expression data. It includes scripts for normalizing the gene expression data and integrating it into the HumanGEM framework to create condition-specific models. Moreover, the protocol includes the script for analyzing genome-scale differential flux across the biochemical network, employing condition-specific models. This analytical phase bridges RNA-Seq data with cellular insights, elucidating altered metabolic activities across diverse conditions. The insights can offer valuable perspectives into the intricate metabolic disturbances that play a pivotal role in cellular homeostasis.</span></p>
Data from: De novo assembly of a tadpole shrimp (Triops newberryi) transcriptome and preliminary differential gene expression analysis
Next-generation sequencing techniques, such as RNA sequencing, have provided a wealth of genomic information for nonmodel species. Transcriptomic information can be used to quantify the patterns of gene expression, which can identify how environmental differences invoke organismal stress responses and provide a gauge in predicting species adaptability. In our study, we used RNA sequencing to characterize the first transcriptome from a naupliar tadpole shrimp (Triops newberryi) to identify the genes expressed during the early life history stages and which could be important for future genomic studies. RNA was extracted from naupliar T. newberryi that were reared in a laboratory-controlled setting and in two different water types, a native and a non-native condition. A total of six replicates, three per condition, were sequenced with the Illumina Hi-Seq 2000 achieving 365 M 50-nt reads. High-quality reads were produced and de novo assembly was used to construct a T. newberryi transcriptome that was approximately 24.8 M base pairs. More than 10 000 peptides were predicted from the assembly, and genes were sorted into gene ontology categories. The use of different water conditions allowed for a preliminary differential gene expression analysis in order to compare the changes in gene expression between conditions. There were 299 differentially expressed genes between water conditions that might serve as a focal point for future genomic studies of Triops acclimation to different environments. The Triops transcriptome could serve as vital genomic information for additional studies on Branchiopod crustaceans.
Data from: Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox (Urocyon littoralis)
The evolutionary mechanisms generating the tremendous biodiversity of islands have long fascinated evolutionary biologists. Genetic drift and divergent selection are predicted to be strong on islands and both could drive population divergence and speciation. Alternatively, strong genetic drift may preclude adaptation. We conducted a genomic analysis to test the roles of genetic drift and divergent selection in causing genetic differentiation among populations of the island fox (Urocyon littoralis). This species consists of six subspecies, each of which occupies a different California Channel Island. Analysis of 5293 SNP loci generated using Restriction-site Associated DNA (RAD) sequencing found support for genetic drift as the dominant evolutionary mechanism driving population divergence among island fox populations. In particular, populations had exceptionally low genetic variation, small Ne (range = 2.1–89.7; median = 19.4), and significant genetic signatures of bottlenecks. Moreover, islands with the lowest genetic variation (and, by inference, the strongest historical genetic drift) were most genetically differentiated from mainland grey foxes, and vice versa, indicating genetic drift drives genome-wide divergence. Nonetheless, outlier tests identified 3.6–6.6% of loci as high FST outliers, suggesting that despite strong genetic drift, divergent selection contributes to population divergence. Patterns of similarity among populations based on high FST outliers mirrored patterns based on morphology, providing additional evidence that outliers reflect adaptive divergence. Extremely low genetic variation and small Ne in some island fox populations, particularly on San Nicolas Island, suggest that they may be vulnerable to fixation of deleterious alleles, decreased fitness and reduced adaptive potential.
Data from: Genomic analysis of a migratory divide reveals candidate genes for migration and implicates selective sweeps in generating islands of differentiation
Differential gene flow, reductions in diversity following linked selection and/or features of the genome can structure patterns of genomic differentiation during the process of speciation. Possible sources of reproductive isolation are well studied between coastal and inland subspecies groups of Swainson's thrushes, with differences in seasonal migratory behaviour likely playing a key role in reducing hybrid fitness. We assembled and annotated a draft reference genome for this species and generated whole-genome shotgun sequence data for populations adjacent to the hybrid zone between these groups. We documented substantial genomewide heterogeneity in relative estimates of genetic differentiation between the groups. Within population diversity was lower in areas of high relative differentiation, supporting a role for selective sweeps in generating this pattern. Absolute genetic differentiation was reduced in these areas, further suggesting that recurrent selective sweeps in the ancestral population and/or between divergent populations following secondary contact likely occurred. Relative genetic differentiation was also higher near centromeres and on the Z chromosome, suggesting that features of the genome also contribute to genomewide heterogeneity. Genes linked to migratory traits were concentrated in islands of differentiation, supporting previous suggestions that seasonal migration is under divergent selection between Swainson's thrushes. Differences in migratory behaviour likely play a central role in the speciation of many taxa; we developed the infrastructure here to permit future investigations into the role several candidate genes play in reducing gene flow between not only Swainson's thrushes but other species as well.
FIGURE 4 in Morphometric analysis to differentiate taxonomically seven species of Eleutherodactylus (Amphibia: Anura: Leptodactylidae) from an Andean cloud forest of Colombia
FIGURE 4. Side of Eleutherodactylus head showing how tympanumeye distance and tympanum diameter were measured.
FIGURE 2. A in Morphometric analysis to differentiate taxonomically seven species of Eleutherodactylus (Amphibia: Anura: Leptodactylidae) from an Andean cloud forest of Colombia
FIGURE 2. A. Cluster analysis CA2. Data set included 58 cases (only adult individuals) and 40 qualitative variables. B. Cluster analysis CA3. Data set included 58 cases (only adult individuals) and the diagnostic variables for the Eleutherodactylus species. In parenthesis, number of individuals of each species.
FIGURE 3. Discriminant analysis. Data set included 140 in Morphometric analysis to differentiate taxonomically seven species of Eleutherodactylus (Amphibia: Anura: Leptodactylidae) from an Andean cloud forest of Colombia
FIGURE 3. Discriminant analysis. Data set included 140 of four species (Eleutherodactylus douglasi, E. merostictus, E. miyatai and E. prolixodiscus) and 11 quantitative variables. The model utilized stepwise discrimination in which all variables were included in the model and then, at each step, the variable that contributed least to the prediction of group memberships was eliminated.
FIGURE 1 in Morphometric analysis to differentiate taxonomically seven species of Eleutherodactylus (Amphibia: Anura: Leptodactylidae) from an Andean cloud forest of Colombia
FIGURE 1. Cluster analysis CA1. Data set included 159 cases (all individuals) and 40 qualitative variables. It was analyzed with Manhattan distances and the UPGMA algorithm; missing data were not substituted. In parenthesis, number of individuals of each species.
Intravoxel incoherent motion model of diffusion weighted imaging and diffusion kurtosis imaging in differentiating of local colorectal cancer recurrence from scar/fibrosis tissue by multivariate logistic regression analysis
<p>We uploaded mean of diffusion coefficient (MD) and mean of diffusional Kurtosis values of 56 patients related to the manuscript: Fusco, Roberta, Vincenza Granata, Mario Sansone, Robert Grimm, Paolo Delrio, Daniela Rega, Fabiana Tatangelo, Antonio Avallone, Nicola Raiano, Giuseppe Totaro, Vincenzo Cerciello, Biagio Pecori, and Antonella Petrillo. 2020. "Intravoxel Incoherent Motion Model of Diffusion Weighted Imaging and Diffusion Kurtosis Imaging in Differentiating of Local Colorectal Cancer Recurrence from Scar/Fibrosis Tissue by Multivariate Logistic Regression Analysis" Applied Sciences 10, no. 23: 8609. https://doi.org/10.3390/app10238609</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.
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.