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65 results for “TCR repertoire”
Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T cell memory formation after mild COVID-19 infection
<p>Processed TCRbeta and TCRalpha repertoires after mild COVID-19 (Version 2.0: day 85 timepoints added) infection, see preprint: <a href="https://www.biorxiv.org/content/10.1101/2020.05.18.100545v3">https://www.biorxiv.org/content/10.1101/2020.05.18.100545v3</a></p> <p>and GitHub repository: <a href="https://github.com/pogorely/Minervina_COVID">https://github.com/pogorely/Minervina_COVID</a></p> <p>Two donors (M and W), two biological replicates of PBMC (F1 and F2), CD4+, CD8+, and Memory subpopulations for each post-infection time points (day 15, 30, 37, 45, 85 post-infection), and pre-infection PBMC repertoires sampled in 2019 and 2018. </p>
Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities: discovery cohort meta data and parsed TCR repertoire data
<p>Meta data corresponding the the discovery cohort for the paper, "Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities" by Magdalena L Russell, Aisha Souquette, David M Levine, Stefan A Schattgen, E Kaitlynn Allen, Guillermina Kuan, Noah Simon, Angel Balmaseda, Aubree Gordon, Paul G Thomas, Frederick A Matsen IV, and Philip Bradley. These meta data include: </p> <p>(1) a file mapping the SNP data subject IDs to the TCR repertoire data subject IDs (gwas_id_mapping.tsv)<br> (2) a file including the PCAir PCs, self-reported ancestry, and genomic ancestry for each subject (all_pc_air.txt)<br> (3) a file including the PCAir variance explained by each PC (all_pc_air_variance.txt)<br> (3) a file including the SNP ID, chromosome, hg19 position, allele, rsid, and quality control metrics for each SNP in the SNP array (emerson_snp_rs_data.tsv)<br> (4) a file including IMGT genes and sequences used for parsing TCRB repertoire data (human_vj_allele_cdr3_nucseqs.tsv)<br> (5) a file including predicted TRBD2 allele genotypes for each subject (emerson_trbd2_alleles.tsv)<br> (6) Parsed TCRB repertoire data. These raw data were first published in Emerson et. al, <em>Nature Genetics </em>2017. (emerson_parsed_tcrb.tgz)</p> <p><strong>Corresponding discovery cohort raw TCR repertoire data is available here: </strong>https: //doi.org/10.21417/B7001Z (ImmuneACCESS database)<br> <strong>Corresponding discovery cohort SNP data is available here:</strong> https: //www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001918.v1.p1 (The database of Genotypes and Phenotypes, accession number: phs001918)<br> <br> <strong>Software tools designed to work with these data are available here:</strong> https://github.com/phbradley/tcr-gwas</p>
Dataset: The TCR repertoire reconstitution in multiple sclerosis: comparing one-shot and continuous immunosuppressive therapies
<p>This dataset, containing TCRbeta-chain data, is the basis for the following publication in Frontiers in Immunology: The TCR repertoire reconstitution in multiple sclerosis: comparing one-shot and continuous immunosuppressive therapies. The file key can be found in the file: file_key.xlsx. Relevant methodological details maybe found in the corresponding publication.</p>
Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities: validation cohort meta data and parsed TCR repertoire data
<p>Meta data corresponding the the validation cohort for the paper, "Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities" by Magdalena L Russell, Aisha Souquette, David M Levine, Stefan A Schattgen, E Kaitlynn Allen, Guillermina Kuan, Noah Simon, Angel Balmaseda, Aubree Gordon, Paul G Thomas, Frederick A Matsen IV, and Philip Bradley. These meta data include: </p> <p>(1) SNP genotypes for the two SNPs which overlap with the discovery cohort<br> - (nicaragua_snp_genotypes_ints.tsv) -- SNP genotypes as integers<br> - (nicaragua_snp_genotypes_strings.tsv) -- SNP genotypes as allele strings <br> (2) the ancestry PCs for each individual in the validation cohort (nicaragua_snp_ancestry_PCA.tsv)<br> (3) a file including IMGT genes and sequences used for parsing TCRB repertoire data (human_vj_allele_cdr3_nucseqs.tsv)<br> (4) a file including IMGT genes used for parsing TCRA repertoire data (human_vj_alleles_alpha.tsv)<br> (5) Parsed TCRA repertoire data (nicaragua_parsed_TCRA.tgz)<br> (6) Parsed TCRB repertoire data (nicaragua_parsed_TCRB.tgz) </p> <p><strong>Corresponding raw validation cohort TCR repertoire data is available here:</strong> https://www. ncbi.nlm.nih.gov/bioproject/PRJNA762269 (The BioProject database, accession number: PRJNA762269)</p> <p><strong>Software tools designed to work with these data are available here:</strong> https://github.com/phbradley/tcr-gwas</p>
Data for "Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed"
<p>This folder holds the data for the paper "Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed" (in submission) More information regarding this paper and the data is given in the GitHub repository (https://github.com/sgielis/WT1_TCR)</p> <p>The raw folder contains all MiXCR files for the two studied WT1 epitopes and two VZV epitopes. The VZV epitopes were not taken into account in this paper, but were used to build VZV-specific TCRex models for another paper [in submission]. Since all TCRs for the 4 epitopes were sequences together, this data was used for quality control purposes as explained in the paper. Following 4 folders are present:</p> <ul> <li>run1: TCR data from the first run for WT1-126, WT1-37 and IE62</li> <li>run1_orf18: TCR data from the first run for ORF18</li> <li>run2: WT1-37 data filtered on high and low threshold gating.</li> <li>run 3: extra TCR data for WT1-126, WT1-37 aligned with MiXCR</li> </ul> <p> </p>
Longitudinal Assessment of TCR Repertoires in Recipients of Inactivated SARS-CoV-2 Vaccines: An Artificial Intelligence-Guided Study
<p>T cells play a crucial role in mitigating disease severity during SARS-CoV-2 infection and in shaping long-term immune memory. However, the precise molecular immune response involving T-cell receptor (TCR) repertoire changes following full vaccination, and evaluating vaccine efficacy through TCR analysis, remains incompletely understood. In this study, we conducted a 10-month longitudinal investigation of individuals who received SARS-CoV-2 inactivated vaccines and developed a vaccine efficacy evaluation model. Through the advanced large language artificial intelligence method, we identified vaccine-specific TCR clones, 3 V genes, 20 V-J combinations, and 3 epitopes, and traced their longitudinal development. The vaccine-specific TCR clones expanded to peak levels after the second vaccine dose and remained detectable in most subjects at 10 months. Utilizing vaccine-specific TCRs as novel markers, we constructed a vaccine efficacy evaluation model that predicts antibody levels with a mean AUC of 0.96, highlighting the relationship between vaccine-specific TCRs and antibodies. Our findings reveal the longitudinal patterns of vaccine-specific TCR clones and the potential of the efficacy evaluation model built upon them.</p>
TCR repertoire sequencing related to "Unique roles of coreceptor-bound LCK in helper and cytotoxic T cells"
<p>This archive contains datasets needed for recapitulating the analysis of TCR repertoires for the manuscript <em>“Unique roles of coreceptor-bound LCK in helper and cytotoxic T cells”</em> by Horkova et al., 2022. The code for the analysis can be found on GitHub: https://github.com/Lab-of-Adaptive-Immunity/lck-tcrseq. Raw data are deposited in the SRA (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA872031).</p> <p>The Zenodo archive contains the following files, which are needed to run the analysis script:</p> <ul> <li>merged outputs from MiXCR <code>merged_TCR_repertoires.csv</code></li> <li>metadata file <code>metadata_Lck.csv</code></li> <li>TRA and TRB repertoires prepared for processing with the Immunarch package <code>immdata_tra.rds</code>, <code>immdata_trb.rds</code></li> </ul>
Murine TCR-beta repertoire sequencing
The purpose of this project was to determine the effects of chronic exposure to unpredictable mild socio-environmental stressors during gestation on the TCR-beta repertoire of newborn mice.
The thymoproteasome hardwires the TCR repertoire of CD8+ T cells in the cortex independent of negative selection
GEO Series GSE164895. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing; Other.
Novel TCR sequencing and cloning methods for sensitive and quantitative interrogation of repertoires and rapid isolation of tumor-reactive TCRs
GEO Series GSE225984. Homo sapiens; Mus musculus. 34 samples. Type: Other.
Assessing the impact of TET2 and TET3 deletion in TCRa and TCRb expression and repertoire in murine CD4 T cells in physiological and pathological conditions [TCR-seq]
GEO Series GSE276582. Mus musculus. 4 samples. Type: Other.
Human thymic putative CD8aa precursors exhibit a biased TCR repertoire in single cell AIRR-seq
GEO Series GSE227408. Homo sapiens. 20 samples. Type: Expression profiling by high throughput sequencing; Other.
Single cell RNA sequencing and TCR repertoire analysis of MIS-C affected patients versus healthy controls and severe adult COVID-19
GEO Series GSE184330. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
High-throughput Ig and TCR repertoire single-cell sequencing analysis in rhesus macaques
GEO Series GSE179722. Macaca mulatta. 5 samples. Type: Expression profiling by high throughput sequencing.
Single Cell Immunophenotyping of Lyme Erythema Migrans (Bulk TCR Repertoire Sequencing)
GEO Series GSE172225. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Single-Cell Analysis of Transcriptome and TCR Sequencing Reveals Immune Cell Atlas and Functional Heterogeneity of T Cell Repertoire in Murine Heart Transplantation
GEO Series GSE249989. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
SLAM/SAP signaling regulates discrete γδ T cell developmental checkpoints and shapes the innate-like γδ TCR repertoire
GEO Series GSE262064. Mus musculus. 12 samples. Type: Other.
Single Cell Immunophenotyping of Lyme Erythema Migrans [Single-Cell TCR Repertoire Sequencing]
GEO Series GSE169438. Homo sapiens. 12 samples. Type: Other.
Blood-Tumor overlapping TCR repertoire predicts the clinical responses of PD-1 blockade in patients with gastrointestinal cancer[RNA-Seq]
GEO Series GSE154538. Homo sapiens. 26 samples. Type: Expression profiling by high throughput sequencing.
TCR repertoire and transcriptomic analyses of advanced solid tumors in first-in-human phase 1 study of IT1208, a defucosylated humanized anti-CD4 depleting antibody
GEO Series GSE120102. Homo sapiens. 124 samples. Type: Expression profiling by high throughput sequencing.
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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.
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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.