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54,099 results for “Expression”
A Bioconductor workflow for processing, evaluating and interpreting expression proteomics data
<p>Files for users of the workflow "A Bioconductor workflow for processing, evaluating and interpreting expression proteomics data". Files include Proteome Discoverer (v2.5) processing and consensus workflows for both TMT and LFQ expression proteomics data. Also provided are the output .txt files of a corresponding Proteome Discoverer identification search, as required for users to follow the workflow themselves. For raw data please refer to PRIDE. Appendix is provided as a PDF.</p>
Plasmid Maps for a Nuclear Transformation Vector in Chlamydomonas reinhardtii for the Expression and Secretion of the Plastic-Degrading Enzyme (PHL7)
<p><strong>pJP32PHL7 Vector:</strong></p> <ul> <li> <p><strong>Size:</strong> 5692 bp</p> </li> <li> <p><strong>Key Features:</strong></p> <ul> <li><strong>HSP70 Promoter:</strong> A heat shock protein promoter fused with the <em>rbcS2</em> promoter to drive expression of downstream genes.</li> <li><strong>Ble Resistance Gene:</strong> Confers resistance to bleomycin, useful for selection in <em>Chlamydomonas reinhardtii</em>.</li> <li><strong>PHL7 Gene:</strong> Encodes the plastic-degrading enzyme PHL7, inserted downstream of the <em>F2A</em> site for expression in the host.</li> <li><strong>Intron Sequences:</strong> Contains multiple <em>rbcS2</em> introns for enhancing expression in <em>Chlamydomonas</em>.</li> <li><strong>Selectable Marker (AmpR):</strong> Confers ampicillin resistance for selection in <em>E. coli</em>.</li> <li><strong>Replication Origin:</strong> Includes <em>ori</em> and <em>F1 ori</em> for replication in <em>E. coli</em>.</li> </ul> <p> </p> </li> <li> <p><strong>Applications:</strong> This vector is designed for nuclear transformation in <em>Chlamydomonas reinhardtii</em>, enabling the expression and secretion of the plastic-degrading enzyme (PHL7) under the control of a hybrid <em>HSP70</em>rbcS2 promoter.</p> </li> </ul> <p><strong>pJP32PHL7dg Vector:</strong></p> <ul> <li> <p><strong>Size:</strong> 5692 bp</p> </li> <li> <p><strong>Key Features:</strong></p> <ul> <li><strong>HSP70 Promoter:</strong> Retains the HSP70 and <em>rbcS2</em> fusion promoter for gene expression.</li> <li><strong>LacZ Alpha Fragment:</strong> Includes a LacZ alpha fragment for blue/white screening.</li> <li><strong>PHL7 Gene:</strong> Encodes the plastic-degrading enzyme PHL7, linked downstream of the <em>F2A</em> site, allowing for expression in the host.</li> <li><strong>Ble Resistance Gene:</strong> Also confers bleomycin resistance for selection in <em>Chlamydomonas</em>.</li> <li><strong>Selectable Marker (AmpR):</strong> Confers ampicillin resistance for selection in <em>E. coli</em>.</li> <li><strong>Intron Sequences:</strong> Contains <em>rbcS2</em> introns for optimizing gene expression in the host organism.</li> </ul> <p> </p> </li> <li> <p><strong>Applications:</strong> The pJP32PHL7dg vector is similarly designed for nuclear transformation in <em>Chlamydomonas reinhardtii.</em> It also facilitates the expression and secretion of the plastic-degrading enzyme PHL7, driven by the hybrid <em>HSP70</em>rbcS2 promoter, but without glycosilation sites.</p> </li> </ul>
Data from: Polymorphic tandem repeats shape single-cell gene expression across the immune landscape
<p>This dataset contains the association summary statistics (v0.1) for genome-wide tandem repeat (TR) expression quantitative trait (eQTL) analysis of TenK10K Phase 1 (https://doi.org/10.1101/2024.11.02.621562). </p> <p>Please access the README for a detailed description of file contents. </p> <p> </p>
Genetic Modulation of Protein Expression in Rat Brain
<p><span>Genetic variations in protein expression are implicated in a broad spectrum of common diseases and complex traits. However, the fundamental genetic architecture and variation of protein expression have received comparatively less attention than either mRNA or classical phenotypes. In this study, we systematically quantified proteins in the brains of a large family of rats using tandem mass tag (TMT)-based quantitative mass-spectrometry (MS) technology. We identified and quantified a comprehensive proteome of 8,119 proteins from Spontaneously Hypertensive (SHR/Olalpcv), Brown Norway with polydactyly-luxate (BN-Lx/Cub), and 29 of their fully inbred HXB/BXH progeny. Differential expression (DE) analysis identified 597 proteins with significant differences in expression between the parental strains (fold change > 2 and FDR < 0.01). We characterized 95 variant peptides by proteogenomics approach and discovered 464 proteins linked to strong <em>cis</em>-acting quantitative trait loci (pQTLs, FDR < 0.05). We also explored the linkage of pQTLs with behavioral phenotypes in rats and examined the sex-specific pQTLs to reveal both distinct and shared <em>cis</em>-pQTLs between sexes. Furthermore, by creating a novel view of the rat pangenome, we improved the ability to pinpoint candidate genes underlying pQTL. Finally, we explored the connection between the pQTLs in rat and human disorders, underscoring the translational potential of our findings. Collectively, this work demonstrates the value of large and systematic proteo-genetic datasets in understanding protein modulation in the brain and its functional linkage to complex central nervous system (CNS) traits.</span><span> </span></p>
Tissue heterogeneity is prevalent in gene expression studies
<p>This archive contains results associated with the publication</p> <p><em>Tissue heterogeneity is prevalent in gene expression studies. Gregor Sturm, Markus List and Jitao David Zhang.</em></p> <p> </p> <ul> <li>expr.tissuemark.affy.roche.symbols.gmt: The tissue signatures from the BioQC publication used in this study</li> <li>gtex_v6_gini_solid.gmt: The cross-platform cross-species validated tissue signatures produced in this study</li> <li>heterogeneity_results.tsv.gz: Signature scores and heterogeneity calls for each tested signature</li> <li>heterogeneity_fractions.tsv: Fraction of heterogeneous and severely heterogeneous samples per tissue</li> </ul>
Mammary single-cell RNA-seq analysis and prostate cancer survival as a function of H2AFJ expression for the paper entitled: The histone variant H2A.J is enriched in luminal epithelial cells
<p>H2A.J is a poorly studied mammalian-specific variant of histone H2A. We used immunohistochemistry to study its localization in various human and mouse tissues. H2A.J showed cell-type specific expression with a striking enrichment in luminal epithelial cells of multiple glands including those of breast, prostate, pancreas, thyroid, stomach, and salivary glands. H2A.J was also highly expressed in many carcinoma cell lines and in particular, those derived from luminal breast and prostate cancer. H2A.J thus appears to be a novel marker for luminal epithelial cancers. Knocking-out the H2AFJ gene in T47D luminal breast cancer cells reduced the expression of several estrogen-responsive genes which may explain its putative tumorigenic role in luminal-B breast cancer.</p>
Analytical expressions for thermophysical properties of solid and liquid aluminum relevant for fusion applications
<p>Aluminum is being actively employed by the fusion community as a non-toxic chemical proxy to beryllium, since both materials form covalent hydrides, high-melting oxides as well as alloys with tungsten [1]. Characteristic examples include studies of in situ cleaning of diagnostic first mirrors [2,3], investigations of hydrogen retention or deposited layer formation [4,5] and experiments dedicated to sputtered material transport in diagnostic ducts [6]. Aluminum has also served as a surrogate for beryllium in high heat flux tests, given its low melting point and low mass density. Characteristic examples concern experiments on the interaction of adhered Al dust with transient and stationary plasmas carried out in Magnum-PSI [7] and the controlled melting of Al blocks exposed in the DIII-D divertor under steady L-mode discharge conditions using the DiMES manipulator [8]. In order to reliably model the macroscopic metallic melt motion realized in the sloped geometry Al L-mode exposures in the DIII-D divertor, the material library of the MEMENTO melt dynamics code, that previously concerned tungsten [9], beryllium [10], niobium [11,12] and iridium [11,12], has to be extended to aluminum.</p> <p>Reliable experimental data have been analyzed for the specific isobaric heat capacity, electrical resistivity, thermal conductivity, mass density, vapor pressure, latent heat of fusion, enthalpy of vaporization, work function, total hemispherical emissivity and absolute thermoelectric power from the room temperature up to the normal boiling point of aluminum as well as for the surface tension and the dynamic viscosity across the liquid state. Analytical expressions are recommended for the temperature dependence of these thermophysical properties, which involve high temperature extrapolations given the absence of extended liquid aluminum measurements. The analytical expressions, the details of their construction and the main references are included in the accompanying pdf.</p> <p>[1] L. Marot, C. Linsmeier, B. Eren, L. Moser, R. Steiner and E. Meyer, "Can aluminium or magnesium be a surrogate for beryllium: A critical investigation of their chemistry", Fus. Eng. Des. 88 (2013) 1718.<br> [2] A. Maffini, L. Moser, L. Marot, R. Steiner, D. Dellasega, A. Uccello, E. Meyer and M. Passoni, "In situ cleaning of diagnostic first mirrors: an experimental comparison between plasma and laser cleaning in ITER-relevant conditions", Nucl. Fusion 57 (2017) 046014.<br> [3] A. Litnovsky, V. S. Voitsenya, R. Reichle et al., "Diagnostic mirrors for ITER: research in the frame of International Tokamak Physics Activity", Nucl. Fusion 59 (2019) 066029.<br> [4] A. Kreter, T. Dittmar, D. Nishijima, R. P. Doerner, M. J. Baldwin and K. Schmid, "Erosion, formation of deposited layers and fuel retention for beryllium under the influence of plasma impurities" Phys. Scr. T159 (2014) 014039.<br> [5] C. Quirós, J. Mougenot, G. Lombardi, M. Redolfi, O. Brinza, Y. Charles, A. Michau and K. Hassouni, "Blister formation and hydrogen retention in aluminium and beryllium: A modeling and experimental approach", Nucl. Mater. Energy 12 (2017) 1178.<br> [6] N. A. Babinov, A. G. Razdobarin, I. M. Bukreev et al, "Three-dimensional modeling of sputtered materials transport in diagnostic ducts of fusion devices", Nucl. Fusion 62 (2022) 126004.<br> [7] S. Ratynskaia, P. Tolias, M. De Angeli, D. Ripamonti, G. Riva, D. Aussems and T. W. Morgan, "Interaction of adhered beryllium proxy dust with transient and stationary plasmas", Nucl. Mater. Energy 17 (2018) 222.<br> [8] D. L. Rudakov, T. Abrams, I. Bykov et al., "Controlled low-Z metal melting in the DIII-D divertor", Abstract submitted for the 19th International Conference on Plasma-Facing Materials and Components for Fusion Applications, 22-26 May 2023, Bonn, Germany.<br> [9] P. Tolias, "Analytical expressions for thermophysical properties of solid and liquid tungsten relevant for fusion applications", Nucl. Mater. Energy 13 (2017) 42.<br> [10] P. Tolias, "Analytical expressions for thermophysical properties of solid and liquid beryllium relevant for fusion applications", Nucl. Mater. Energy 31 (2022) 101195.<br> [11] P. Tolias, S. Ratynskaia and K. Paschalidis, "Thermophysical properties for the published article - Experiments and modelling on ASDEX Upgrade and WEST in support of tool development for tokamak reactor armour melting assessments", Zenodo. https://doi.org/10.5281/zenodo.6778824.<br> [12] S. Ratynskaia, K. Paschalidis, P. Tolias et al., "Experiments and modelling on ASDEX Upgrade and WEST in support of tool development for tokamak reactor armour melting assessments", Nucl. Mater. Energy 33 (2022) 101303.<br> </p>
Tumor MHC Class I Expression Associates with Interleukin-2 Response in Melanoma
<p>The processed multiplexed IF data and sample ID corresponding to the raw data in record (https://zenodo.org/record/4300912#.Y-WGBuzMKY-). All code used to produce the results of this study are available at <a href="https://github.com/cBio-MSKCC/Halo_Melanoma_IL2">https://github.com/cBio-MSKCC/Halo_Melanoma_IL2</a>.</p>
The spatial landscape of gene expression isoforms in tissue sections
<p><strong>This upload provides raw in situ sequencing (ISS) data used to validate Spatial Isoform Transcriptomics (SiT), as well as R scripts required for SiT analysis.</strong></p> <p><strong>GenePlots.zip and Reads.zip are ISS data </strong><strong>generated and collected by the CARTANA ISS service</strong>. <strong>The following data description is cited from the report provided by CARTANA ISS service:</strong></p> <p><em>"Folder "Reads" contains coordinates and gene information of segmented spots.<br> The coordinates are in pixel unit. Scaling factor is 0.32 um/pixel. (0,0) is at northwest (top-left corner).<br> With Low/High Threshold, we refer to the quality thresholding. Our technology is fluorescence based, i.e. with the thresholding one can balance how certain the signals are.</em></p> <p><em>Files ending with _LowThreshold: reads not matching with any known barcode were already discarded.</em></p> <p><em>Files ending with _HighThreshold: has information only about spots that passed additional quality check.</em></p> <p><em>Folder "GenePlots" has plotted images in static .png format, fully zoomed out. LowThreshold and HighThreshold follow the same thresholding strategy as in reads files."</em></p> <p> </p> <p><strong>SiT-master.zip is a download of the GitHub repository </strong><a href="https://github.com/ucagenomix/SiT">https://github.com/ucagenomix/SiT</a>, <strong>providing figures and analysis scripts for SiT.</strong></p> <p> </p> <p><strong>Related SiT data are deposited through GEO, accession number <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE153859">GSE153859</a></strong></p>
KG for heart failure gene expression data
<p>Pre processed gene expression data for different heart failure. Includes count table, gene patiens metadata, gene lenght</p>
Differential response of α-synuclein expression to bacterial ligands and metabolites in mouse enteroendocrine cells
<p>Dataset for manuscript <em>"<strong> </strong></em><strong>α</strong><strong>-synuclein expression in response to bacterial ligands and metabolites in gut enteroendocrine cells</strong><em>". </em>Tabs in excel file are title with the figure number. </p>
Master Coral database used in USVI SCTLD Transmission Experiment Gene Expression Analysis
<p>The Master Coral Database fasta file is comprised of previously published genome-derived predicted gene models and transcriptomes spanning a wide diversity of coral families. Transcriptomes are from Davies et al., 2016 (doi: 10.3389/fmars.2016.00112), Kirk et al., 2018 (DOI: 10.1111/mec.14934); Moya et al., 2012 (doi: 10.1111/j.1365-294X.2012.05554.x); van de Water et al., 2018 (DOI: 10.1111/mec.14489).</p>
Genome-wide characterization of human minisatellite VNTRs: population-specific alleles and gene expression differences
<p>This repository consists of minisatellite VNTR genotypes for 2,800 samples (2,770 individuals). The raw VCF files were produced using <a href="https://github.com/yzhernand/VNTRseek">VNTRseek</a> on xxx data sources: <a href="http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/">30 high coverage WGS datasets</a> from the 1000 Genomes Project phase 3, <a href="https://www.internationalgenome.org/data-portal/data-collection/30x-grch38">2,504 unrelated genomes</a> from New York Genome Center (NYGC), <a href="https://www.internationalgenome.org/data-portal/data-collection/sgdp">253 genomes from Simons Diversity Genome Project</a> (SGDP), <a href="https://www.illumina.com/products/by-type/informatics-products/basespace-sequence-hub/apps/tumor-normal.html">two tumor-normal breast cancer samples</a> from Illumina Basespace, haploid genomes <a href="https://www.ncbi.nlm.nih.gov/sra/SRX652547">CHM1 </a>and <a href="https://www.ncbi.nlm.nih.gov/sra/SRX1009644">CHM13</a>, and seven genomes from the Personal Genome Project from the Genome In A Bottle Consortium (GIAB). Raw VCF files are provided for each data source separately.</p> <p>The raw VCF files were preprocessed (preprocess.sh) to extract genotypes and provided in VNTRseek_preprocessed_data.tar.gz (uncompressed size 10G). The R Markdown code to analyze the preprocessed data and produce figures and tables is also provided (tables_and_figures.Rmd). For more information see the ReadMe file.</p> <p>This work was supported in part by NSF grants IIS-1423022 and DBI-1559829.</p>
Hypergraph Factorisation Expression Quantitative Trait Loci
<p>Please cite:</p> <pre><code>Hypergraph factorisation for multi-tissue gene expression imputation. Vinas Torne, Ramon and Joshi, Chaitanya K. and Georgiev, Dobrik and Lin, Phillip and Dumitrascu, Bianca* and Gamazon, Eric* and Lio, Pietro*. *Co-corresponding authors. </code></pre>
Light and confocal micrographs on the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, the accumulation of lipid droplets, and the heterologous expression and localisation of signature LD protein homologs to tobacco pollen tubes
<p>These micrographs accompany the work "Environmental gradients reveal stress hubs predating plant terrestrialization", posted as a pre-print on bioRxiv https://doi.org/10.1101/2022.10.17.512551 </p> <p>The light and confocal micrographs show the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, especially their accumulation of lipid droplets (LDs); in confocal micrographs, LDs appeared as distinct structures upon staining with BODIPY.</p> <p>Further confocal micrographs show the heterologous expression and localisation of signature LD protein homologs detected in Mesotaenium endlicherianum SAG 12.97; heterologous expression was carried out in tobacco pollen tubes were also stained with BODIPY and proteins were tagged with mCherry.</p>
Japanese Expressions Dataset from Human Rights Infringement on Internet
<p>Japanese Expressions Dataset from Human Rights Infringement on Internet</p> <p>これは、言語処理学会2023において”<a href="https://www.anlp.jp/proceedings/annual_meeting/2023/pdf_dir/D2-2.pdf"><strong>権利侵害と不快さの間:日本語人権侵害表現データセット</strong></a>”の発表で用いた、誹謗中傷等の表現を集めたデータセットです。</p> <p>仕様は変更される可能性があります</p> <p>Release Date</p> <p>Version 0.1 2023/03/09</p> <p>Version 0.2 2023/06/01</p> <p> </p> <p>1.調査対象</p> <p>民事事件</p> <ul> <li>発信者情報開示請求事件</li> <li>損害賠償等請求事件</li> </ul> <p>インターネット上の投稿による人権侵害を争った事件よりこのデータセットは作成されています。</p> <p>Annotation Scheme</p> <p>1: Text in Dispute </p> <p>Text in Dispute is transcribed from the list of articles submitted or the facts and reasons section of the court cases.<br> This text is what the plaintiff alleges is infringing his or her rights.<br> <br> For example, we use the tag [Plaintiff] for descriptions related to plaintiffs, the tag [Defandant] for descriptions related to defandantss and [Third Party] for any mention of third parties.<br> The tag [Other] is designated for texts involving anonymized place names and any other content not covered by the preceding tags. <br> If distinguishing between tags proves challenging, we advise the use of [Other]. <br> Should a URL be present in the text, it is substituted with the [URL] tag.</p> <p>2: Context Utilized in Adjudication</p> <p>In some cases, the history of the conversation and previous postings are taken into account in determining whether or not an infringement has occurred.<br> Such text is transcribed from the fact-finding and judgment portions of the court case.<br> Contextual information that can be used for tasks other than proper understanding of the issue and accurate learning and classification.<br> Anonymization is applied in the same way as for [1: Text in Dispute].</p> <p>3: Allegedly Infringed Right and Judgement on the Infringement Allegation</p> <p>This category provides a label indicating the types of personal rights infringement complained of by the plaintiff against Text in Dispute and whether or not the infringement of that right was recognized by the trial court.<br> If there are more than two types of infringement of rights complained of by the plaintiff against one text, up to two labels are given.</p> <p>3-1a: The types of Allegedly Infringed Right 1</p> <p>Labels are assigned from the above types of personal rights, the right of reputation, the sense of honor, the right of peaceful private life, and other personal rights, from the complaint of infringement of rights by the plaintiff.</p> <p>3-1b: Judgement on the Infringement Allegation 1</p> <p>This category indicates whether the trial court granted the plaintiff's complaint against the text under consideration.<br> The annotator reads the result of the Judgement for each case from the court's judgment in the case.<br> If we find that the court has admitted the plaintiff's claim, we assign "1" label to the case concerning the infringement of personal rights.<br> If we find that the court has dismissed the plaintiff's claim, we assign "0" label to those cases that are not infringing.<br> We assign the label "UNJUDGE" to cases where we cannot find the court's Judgement. <br> This appears in cases where the plaintiff alleges multiple infringements and only one of the claims is adjudicated, or where the complaint is found to have been dismissed based on factors other than a determination of infringement by textual expression.</p> <p>3-2a & b:The types of Allegedly Infringed Right and Judgement on the Infringement Allegation 2</p> <p>If two infringements are complained of, the annotator assigns a label for the second right.</p> <p><br> 4: Index Information of Court Cases</p> <p>This section contains information about the cited court case.</p> <p>4-1: Case Number</p> <p>This is the case number of the court case and the court in which the case was argued.</p> <p>4-2: Case Name</p> <p>This is the case name of the court case and the court in which the case was argued.<br> Either a case requesting for disclosure of sender's information. or a case requesting compensation for damages is applicable.</p> <p>4-3: Bibliography</p> <p>This is the bibliography of the cited case.</p> <p>4-4: Article Number</p> <p>This is the number assigned to Text in Dispute in the court case.</p> <p>4-5: Online Platform</p> <p>If the online platform where Text in Dispute is explicitly indicated in the court case, it is stated.<br> Since the form of the text and context differs from platform to platform, considering the uniqueness of each service is an important factor to be taken into account.</p>
Datasets, reproducible codes, and results for evaluating differential expression analysis methods on population-level RNA-seq data
<p>This upload contains the necessary R codes and data to reproduce the FDR and Power results described in our correspondence "Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false positives" to Li Y, Ge X, Peng F, Li W, Li JJ, Exaggerated false positives by popular differential expression methods when analyzing human population samples, <em>Genome Biology</em> 23, 79, 2022, DOI: 10.1186/s13059-022-02648-4.</p>
Supplementary Tables for Expression of cell-wall related genes is highly variable and correlates with sepal morphology
<p>Supplementary Information and script for "Expression of cell-wall related genes is highly variable and correlates with sepal morphology"</p> <p>R scripts for analysis</p> <p>Data necessary to run analyses</p> <p>Generated data</p> <p>Supplementary Tables</p> <p> </p>
Paired differential gene expression and splicing analyses results of 199 baseline vs. case comparisons across 100 datasets
<p>This dataset contains results from paired differential expression and differential splicing analyses as well as gene-set over-representation analysis results for 199 baseline vs. case comparisons across 100 randomly curated datasets with accompanying metadata (<a href="https://doi.org/10.1186/s12915-023-01724-w" target="_blank" rel="noopener">article</a>).<br>All results were computed using the R package <a href="https://github.com/shdam/pairedGSEA">pairedGSEA</a>, which utilized DESeq2 (Love et al., 2014), DEXSeq (Anders et al., 2012), and fgsea (Korotkevich et al., 2019).<br>See limma results here: <a href="https://doi.org/10.5281/zenodo.8162214">https://doi.org/10.5281/zenodo.8162214</a><br><br>Each .RDS file contains a list with four objects: A 'metadata' object with the metadata of the respective raw data, a 'genes' object with gene-level differential splicing and expression results, a 'gene_set' object with over-representation results, and 'experiment' with the experiment title.<br><br>The filenames follow this pattern: "[dataset ID]_[GEO accession number]_[Manually assigned comparison title].RDS".<br><br>All datasets were obtained from a local copy of the ARCHS4 v11 database of transcript counts (Lachmann et al., 2018).</p>
TCGA Gene Expression Datasets
<p><strong>Abstract:</strong></p> <p>The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. These datasets contain gene expression profiles of bladder urothelial carcinoma (BLCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), glioblastoma multiforme (GBM), head & neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), and lower grade glioma (LGG).</p> <p>The gene expression profiles for BLCA, CESC, HNSC, KIRC, and LGG were measured experimentally using the Illumina HiSeq 2000 RNA Sequencing platform by the University of North Carolina TCGA genome characterization center. The gene expression profile of the GBM dataset was measured experimentally using the Affymetrix HT Human Genome U133a microarray platform by the Broad Institute of MIT and Harvard University cancer genomic characterization center.</p> <p><strong>Inspiration:</strong></p> <p>This dataset was uploaded to UBRITE for GTKB project. </p> <p><strong>Instruction:</strong></p> <p>The log<sub>2</sub>(x+1) normalization was removed, and z-normalization was performed on the BLCA, CESC, HNSC, KIRC, and LGG datasets.</p> <p>The log<sub>2</sub>(x) normalization was removed, and z-normalization was performed on the GBM dataset.</p> <p><strong>Acknowledgments:</strong></p> <p>Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8.</p> <p>The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764.</p> <p><strong>U-BRITE last update: </strong>07/13/2023</p>
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.