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2 results for “tensor decomposition”
Datasets for Muscle : semi-non negative joint decomposition of multiple single cell tensors
<p>This link contains the processed single cell Hi-C (scHi-C) and DNA methylation datasets of <a href="https://www.nature.com/articles/s41592-019-0502-z">Li et al. 2019</a> and <a href="https://www.nature.com/articles/s41586-020-03182-8">Liu et al. 2021. </a>in two separate folders. The datasets are used for the <a href="https://github.com/kp223/Muscle">Github page</a> of <a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=gUgGLY0AAAAJ&citation_for_view=gUgGLY0AAAAJ:u5HHmVD_uO8C">Muscle</a>, which employs a semi-non negative joint tensor decomposition framework for multi-omics data analysis, incorporating scHi-C tensors. The datasets are uploaded in '.qs' format in R (gzipped for the Liu et al. 2021 data), and the chromosome size files are in text format. Further details about the data can be found on the GitHub page. The files </p>
Simultaneous acclimation to nitrogen and iron scarcity in open ocean cyanobacteria revealed by sparse tensor decomposition of metatranscriptomes
<h2>Description</h2> <p>This dataset contains all of the supplementary files necessary to reproduce the findings published in the research article entitled <em>Simultaneous acclimation to nitrogen and iron scarcity in open ocean cyanobacteria revealed by sparse tensor decomposition of metatranscriptomes. </em>The scripts necessary for reproducing the published analyses can be found in the <a href="https://github.com/blasks/barnacle-manuscript">GitHub repository associated with the article</a>. Below is the article abstract and a description of the files included in this dataset.</p> <h2>Abstract</h2> <p>Microbes respond to changes in their environment by adapting their physiology through coordinated adjustments to the expression levels of functionally related genes. To detect these shifts in situ, we developed a sparse tensor decomposition method that derives gene co-expression patterns from inherently complex whole community RNA-sequencing data. Application of the method to metatranscriptomes of the abundant marine cyanobacteria <em>Prochlorococcus</em> and <em>Synechococcus</em> identified responses to scarcity of two essential nutrients, nitrogen and iron, including increased transporter expression, restructured photosynthesis and carbon metabolism, and mitigation of oxidative stress. Further, expression profiles of the identified gene clusters suggest that both cyanobacteria populations experience simultaneous nitrogen and iron stresses in a transition zone between North Pacific oceanic gyres. The results demonstrate the power of our approach to infer organism responses to environmental pressures, hypothesize functions of uncharacterized genes, and extrapolate ramifications for biogeochemical cycles in a changing ecosystem.</p> <h2>Legends for data S1 to S11</h2> <h3>Data S1. <em>Prochlorococcus</em> component profiles.</h3> <p>Median weight profiles for each <em>Prochlorococcus</em> component, including list of associated CyCOGs with corresponding gene weight, bootstrap support, and consensus annotation.</p> <h3>Data S2. <em>Synechococcus</em> component profiles.</h3> <p>Median weight profiles for each <em>Synechococcus</em> component, including list of associated CyCOGs with corresponding gene weight, bootstrap support, and consensus annotation.</p> <h3>Data S3. Enrichment analysis.</h3> <p>Significantly enriched KEGG pathways associated with each component, and compiled consensus annotations for each CyCOG.</p> <h3>Data S4. MED4 CyCOGs.</h3> <p>Mapping of <em>Prochlorococcus</em> MED4 genes to associated CyCOGs.</p> <h3>Data S5. Nitrogen and iron acclimation clusters.</h3> <p>CyCOGs, genes, and annotations for clusters associated with acclimation to nitrogen and iron scarcity.</p> <h3>Data S6. Sample metadata.</h3> <p>Metadata file detailing sampling conditions for all metatranscriptomes used in this study.</p> <h3>Data S7. Genome metadata.</h3> <p>Metadata file for CyCOG v6 reference genomes, including updated clade assignments.</p> <h3>Data S8. CyCOG v6 database.</h3> <p>Tarball of CyCOG v6 database, including reference genomes and annotation data.</p> <h3>Data S9. Reference sequence phylogenies.</h3> <p>Tarball of <em>Prochlorococcus</em> and <em>Synechococcus</em> reference genome phylogenies, used to update clade assignments.</p> <h3>Data S10. <em>Prochlorococcus</em> transcript abundance data.</h3> <p>A netCDF file of raw and normalized <em>Prochlorococcus</em> transcript abundance data, aggregated by CyCOG and organized into an `xarray.Dataset' tensor data structure.</p> <h3>Data S11. <em>Synechococcus</em> transcript abundance data.</h3> <p>A netCDF file of raw and normalized <em>Synechococcus</em> transcript abundance data, aggregated by CyCOG and organized into an `xarray.Dataset' tensor data structure.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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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.