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99 results for “GTEx”

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zenodo48/100

GTEx analysis for the paper entitled: The histone variant H2A.J is enriched in luminal epithelial gland 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>

opencc-by-4.0Sep 2021View details →
zenodo44/100

SWAM model from GTEx dataset

<p>The SWAM models for each GTEx tissue v6 and v8 are publicly available at https://doi.org/10.5281/zenodo.5866500 . These models are trained from GTEx PrediXcan models across all tissues, targeting each tissue type, and formatted in a format that can be directly used by the PrediXcan software tool. See&nbsp;https://github.com/aeyliu/SWAM and https://github.com/aeyliu/SWAM-manuscript for the detailed code to reproduce these resources. More comprehensive information will be available when this resource is linked with a peer-reviewed publication.</p>

opencc-by-4.0Jan 2022View details →
zenodo44/100

Data used in ECLIPSER methods paper and GTEx snRNA-seq cross-tissue reference map analysis

<p>The tables were used in the papers: Rouhana*, Wang* <em>et al.,</em>&nbsp;ECLIPSER: identifying causal cell types and genes for complex traits through single cell enrichment of e/sQTL-mapped genes in GWAS loci, bioRxiv 2021, doi: https://doi.org/10.1101/2021.11.24.469720; and Eraslan&nbsp;<em>et al.,</em>&nbsp;Single-nucleus cross-tissue molecular reference maps to decipher disease gene function, bioRxiv 2021,&nbsp;doi: https://doi.org/10.1101/2021.07.19.452954. &#39;<a href="https://zenodo.org/api/files/1f8d48d0-6bf7-4bec-b6ef-5c7a9ead8079/GTEx_v8_HG38_all_variants.tsv.gz">GTEx_v8_HG38_all_variants.tsv.gz</a>&#39; is&nbsp;an input file for running GWASvar2gene on GTEx v8 eQTLs and sQTLs, and all other files are input files for&nbsp;ECLIPSER.</p>

opencc-by-4.0Nov 2021View details →
zenodo44/100

GTEx exon-level expression summaries for Snaptron

<p>GTEx exon-level expression summary from the Snaptron collection. &nbsp;Format is a tab-separated text file compressed and indexed using BGZip, along with supplementary files containing a Tabix index for the data (ending in tbi) as well as two files describing the samples represented in the columns of the data file (ending in tsv). &nbsp;Uses GENCODE v25 annotation for quantification. &nbsp;Source data for the quantification are the bigWig files produced as part of recount2. &nbsp;More information at http://snaptron.cs.jhu.edu.</p>

opencc-by-4.0Feb 2019View details →
zenodo44/100

GTEx gene-level expression summary for Snaptron

<p>GTEx gene-level expression summary from the Snaptron collection. &nbsp;Format is a tab-separated text file compressed and indexed using BGZip, along with supplementary files containing a Tabix index for the data (ending in tbi) as well as two files describing the samples represented in the columns of the data file (ending in tsv). &nbsp;Uses GENCODE v25 annotation for quantification. &nbsp;Source data for the quantification are the bigWig files produced as part of recount2. &nbsp;More information at http://snaptron.cs.jhu.edu.</p>

opencc-by-4.0Feb 2019View details →
zenodo44/100

GTEx exon-exon-junction-level expression summary for Snaptron

<p>GTEx exon-level expression summary from the Snaptron collection. &nbsp;Format is a tab-separated text file compressed and indexed using BGZip, along with supplementary files containing a Tabix index for the data (ending in tbi) as well as two files describing the samples represented in the columns of the data file (ending in tsv). &nbsp;Uses Rail-RNA for spliced alignment. &nbsp;More information at http://snaptron.cs.jhu.edu.</p>

opencc-by-4.0Feb 2019View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Small_Intestine_Terminal_Ileum

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Kidney Cortex

<p>The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.</p>

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Kidney_Cortex

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Heart_Left_Ventricle

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Brain_Putamen_basal_ganglia

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Brain_Frontal_Cortex_BA9

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Brain_Cerebellum

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Brain_Caudate_basal_ganglia

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Brain_Substantia_nigra

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Cells_Cultured_fibroblasts

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Brain_Hypothalamus

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Colon_Transverse

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Artery_Tibial

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →
zenodo40/100

Full summary statistics of mixQTL for GTEx v8 Adipose_Subcutaneous

The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.

opencc-zeroSep 2020View details →

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DANDI Archive for NWB datasets

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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.

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OpenNeuro

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Last verified 2026-04-29Open record