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16 results for “Inter-individual Variability”
The human Voice Areas: spatial organisation and inter-individual variability in temporal and extra-temporal cortices
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Intra and Inter-Individual Variability in Functional Connectomes of Patients with First Episode of Psychosis
<p>Test-retest functional connectomes for 32 Healthy Controls and 30 First Episode of Psychosis patients. This dataset was originally used in the following article:</p> <p><strong>(Preprint)</strong> Tepper, Ángeles and Núñez, Javiera Vásquez and Ramirez-Mahaluf, Juan Pablo and Aguirre, Juan Manuel and Barbagelata, Daniella and Maldonado, Elisa and Dellarossa, Camila Díaz and Nachar, Ruben and Gonzalez-Valderrama, Alfonso and Undurraga, Juan and Goñi, Joaquín and Crossley, Nicolas, Intra and Inter-Individual Variability in Functional Connectomes of Patients with First Episode of Psychosis. Available at SSRN: <a href="https://ssrn.com/abstract=4241607">https://ssrn.com/abstract=4241607</a> or <a href="http://dx.doi.org/10.2139/ssrn.4241607">http://dx.doi.org/10.2139/ssrn.4241607</a></p> <p>More details and python code used for analyses can be found in this<strong> <a href="https://github.com/angietep/Inter-and-Intra-Indiv-Variability">GitHub repository</a></strong></p>
Consistent inter-individual variability in movement traits shapes the wild boar movement syndrome
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Data from: Selective increases in inter-individual variability in response to environmental enrichment in female mice
One manifestation of individualization is a progressively differential response of individuals to the non-shared components of the same environment. Individualization has practical implications in the clinical setting, where subtle differences between patients are often decisive for the success of an intervention, yet there has been no suitable animal model to study its underlying biological mechanisms. Here we show that enriched environment (ENR) can serve as a model of brain individualization. We kept 40 isogenic female C57BL/6JRj mice for 3 months in ENR and compared these mice to an equally sized group of standard-housed control animals, looking at the effects on a wide range of phenotypes in terms of both means and variances. Although ENR influenced multiple parameters and restructured correlation patterns between them, it only increased differences among individuals in traits related to brain and behavior (adult hippocampal neurogenesis, motor cortex thickness, open field and object exploration), in agreement with the hypothesis of a specific activity-dependent development of brain individuality.
Inter-individual gene expression variability implies stable regulation of brain-biased genes across organs
<div> <div> <h2>Abstract</h2> <a href="https://github.com/christabel-bucao/fish-variability-across-organs/#abstract"></a></div> <p>Phenotypic variation among individuals plays a key role in evolution, since variation provides the material on which natural selection can act. One important link between genetic and phenotypic variation is gene expression. As for other phenotypes, the range of accessible expression variation is limited and biased by different evolutionary and developmental constraints. Gene expression variability broadly refers to the tendency of a gene to vary in expression (i.e., between individuals or cells) due to stochastic fluctuations or differences in genetic, epigenetic, or environmental factors, separately from the differences between e.g. organs. Variability due to biomolecular stochasticity (transcriptional ‘noise’) and cell-to-cell heterogeneity has been well-studied in isogenic populations of unicellular organisms such as bacteria and yeasts. However, for more complex organisms with multiple cells, tissues, and organs sharing the same genetic background, the interplay between inter-individual expression variability, gene and organ function, and gene regulation remains an open question. In this study, we used highly multiplexed 3’-end Bulk RNA Barcoding and sequencing (BRB-seq) to generate transcriptome profiles spanning at least nine organs in outbred individuals of three ray-finned fish species: zebrafish, Northern pike, and spotted gar. For each condition, we measured expression variation per gene independent of mean expression level. We observed that lowly variable genes are enriched in cellular housekeeping functions whereas highly variable genes are enriched in stimulus-response functions. Furthermore, genes with highly variable expression between individuals evolve under weaker purifying selection at the coding sequence level, indicating that intra-species gene expression variability predicts inter-species protein sequence divergence. Genes that are broadly expressed across organs tend to be both highly expressed and lowly variable between individuals, whereas organ-biased genes are typically highly variable within their top organ of expression. For genes with organ-biased expression profiles, we inferred differences in selective pressure on gene regulation depending on their top organ. We found that genes with peak expression in the brain have low inter-individual expression variability across non-nervous organs, suggesting stabilizing selection on regulatory evolution of brain-biased genes. Conversely, liver-biased genes have highly variable expression across organs, implying weaker regulatory constraints. These patterns show that gene regulatory mechanisms evolved differently based on constraints on the primary organ.</p> <h2>Directory Structure</h2> </div> <ul> <li> <p><code>config/</code>: Contains YAML file indicating package versions for conda environment</p> </li> <li> <p><code>data/</code>: Contains input data</p> <ul> <li><code>counts/</code>: Contains counts and UMI-deduplicated counts. Currently under embargo and will be made available upon acceptance for publication.</li> <li><code>gene_metadata/</code>: Contains gene biotype information from Ensembl</li> <li><code>sample_metadata/</code>: Contains sample metadata files for each species</li> <li><code>selectome/</code>: Contains selection statistics from the <a href="https://selectome.org/" rel="nofollow">Selectome</a> database<br><br></li> </ul> </li> <li> <p><code>results/</code>: Contains output files sorted by subfolders labeled after each step of the analysis pipeline. Only R notebook HTML files are available on the Git repository, please check Zenodo for R data files.</p> <ul> <li><code>run_pipeline.Rdata</code>: Contains all parameters used for each step of the analysis pipeline<br><br></li> </ul> </li> <li> <p><code>workflow/</code>: Contains scripts used for the analysis pipeline</p> <ul> <li><code>analysis/</code>: Contains all steps of the analysis pipeline, available as .Rmd files</li> <li><code>functions/</code>: Contains all functions used for analysis/</li> <li><code>renv/</code>: Used for package management in R</li> <li><code>run_pipeline.R</code>: Runs all the steps under analysis/</li> <li><code>run_go_figure.sh</code>: Runs <a href="https://gitlab.com/evogenlab/GO-Figure" rel="nofollow">GO-Figure!</a> 1.0.0 (downloaded separately)</li> <li><code>demultiplex_brbseq_fastq.sh</code>: Used for demultiplexing BRB-seq fastq files using <a href="https://github.com/DeplanckeLab/BRB-seqTools">BRB-seqTools</a> 1.6.1 (downloaded separately) for uploading to NCBI SRA</li> <li><code>rename_fastq_files.sh</code>: Used for renaming demultiplexed fastq files by mapping each barcode to their corresponding sample name</li> <li><code>renv.lock</code>: Lockfile for managing R package versions. Run <code>renv::restore()</code> to set up the R environment based on packages specified in the lockfile. All package versions used are also specified in the output HTML files under results/.</li> </ul> </li> </ul> <div> <h2>Species Codes</h2> </div> <ul> <li><strong>LOC</strong>: <em>Lepisosteus oculatus</em> (spotted gar)</li> <li><strong>ELU</strong>: <em>Esox lucius</em> (Northern pike)</li> <li><strong>DRE</strong>: <em>Danio rerio</em> (zebrafish)</li> </ul>
Variability of Daily Iodine Intake: The Effects of Intra- and Inter-individual Variability in Iodine Nutrition Studies
ClinicalTrials.gov study NCT03731312. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Investigating Inter-individual Variability in Glycemic and Insulin Responses
ClinicalTrials.gov study NCT01804738. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Data from: Selective increases in inter-individual variability in response to environmental enrichment in female mice
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Data from: Phenotypic determinants of inter-individual variability of litter consumption rate in a detritivore population
Abstract not entered
Data from: Phenotypic determinants of inter-individual variability of litter consumption rate in a detritivore population
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Widespread inter-individual gene expression variability in Arabidopsis thaliana
GEO Series GSE115583. Arabidopsis thaliana. 168 samples. Type: Expression profiling by high throughput sequencing.
Measurement of inter-individual variability in gene expression in mouse neutrophils
GEO Series GSE59549. Mus musculus. 10 samples. Type: Expression profiling by array.
Inter-individual variability in lymphocyte stimulation and transcriptomic response predicts mycophenolic acid sensitivity in healthy volunteers
GEO Series GSE141026. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
Human alveolar macrophage response to Mycobacterium tuberculosis: immune characteristics underlying large inter-individual variability.
GEO Series GSE223863. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
Inter-individual variability of early life stages of a model marine invertebrate with a bi-phasic life cycle is shaped by contrasting oceanographic conditions
<p>The datasets represent the data collected from adult females and from megalopae used in the study.</p>
Inter-individual variability in gene expression profiles in human hepatocytes and comparison with HepaRG cells
GEO Series GSE41289. Homo sapiens. 33 samples. Type: Expression profiling by array.
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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.