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accession-icon GSE13381
Detailed transcriptome atlas of the pancreatic beta cell
  • organism-icon Rattus norvegicus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

The aim of the present study was to explore the transcriptome of pancreatic islets and, based on this information, to prepare a comprehensive and open access inventory of insulin-producing -cell gene expression, the beta-Cell Gene Atlas (BCGA).

Publication Title

Detailed transcriptome atlas of the pancreatic beta cell.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP181957
Molecular basis of neuronal subtype bias introduced by proneural factors Ascl1 and Neurog2 (single-cell RNA-seq)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Basic helix-loop-helix (bHLH) proneural transcription factors (TFs) Ascl1 and Neurog2 are integral to the development of the nervous system. Here, we investigated the molecular mechanisms by which Ascl1 and Neurog2 control the acquisition of generic neuronal fate and impose neuronal subtype identity. Using direct neuronal programming of embryonic stem cells, we found that Ascl1 and Neurog2 regulate distinct targets by binding to largely different sets of sites. Their divergent binding pattern is not determined by the previous chromatin state but distinguished by specific E-box enrichments which reflect the DNA sequence preference of the bHLH domain. The divergent Ascl1 and Neurog2 binding patterns result in distinct chromatin accessibility and enhancer activity landscapes that shape the binding and activity of downstream TFs during neuronal specification. Our findings suggest that proneural factors contribute to neuronal diversity by differentially altering the chromatin landscapes that shape the binding of neuronally expressed TFs. Overall design: Single-cell RNA-seq was used to characterize gene expression in mixed populations of mES cells containing induced expression of either Ascl1 or Neurog2.

Publication Title

Proneural factors Ascl1 and Neurog2 contribute to neuronal subtype identities by establishing distinct chromatin landscapes.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE21682
Gene expression study of macrophages during early foreign body reaction
  • organism-icon Rattus norvegicus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Foreign body reaction (FBR), initiated by adherence of macrophages to biomaterials, is associated with several complications.

Publication Title

Gene expression study of monocytes/macrophages during early foreign body reaction and identification of potential precursors of myofibroblasts.

Sample Metadata Fields

Specimen part

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accession-icon GSE99941
Effects of PPARgamma-inactive Delta-2-TGZ on breast cancer cells MCF-7
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

TGZ is an agonist of the nuclear receptor PPARgamma. This synthetic compound displays anticancer effects on breast cancer cells but some of them are PPARgamma independent. Delta-2-TGZ (delta-2-troglotazone) is a PPARgamma inactive TGZ derivative possessing a double bond adjoining the thiazolidinedione ring. This compound still displays anticancer efefcts. It is an interesting tool to study the PPARgamma-independent mechanisms.

Publication Title

Pro-apoptotic effect of Δ2-TGZ in "claudin-1-low" triple-negative breast cancer cells: involvement of claudin-1.

Sample Metadata Fields

Cell line

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accession-icon GSE113624
Gene expression profiles of tumor-induced pTregs and anergic tumor-specific CD4+ T cells
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

Up to now the role of tumor-specific pTregs and anergic cells during tumor development is not fully understood. Here we used a genetically-induced tumor expressing a MHC-II restricted DBY model antigen to characterize the tumor-induced pTregs and anergic cells that arise early during tumor development.

Publication Title

Induction of anergic or regulatory tumor-specific CD4<sup>+</sup> T cells in the tumor-draining lymph node.

Sample Metadata Fields

Time

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accession-icon GSE113623
Gene expression profile of tumor antigen-specific CD4 T cells
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

Up to know CD4 T cell antitumor responses have been mostly studied in transplanted tumor models. However, although they are valuable tools, they are not suitable to study the long term interactions between tumors and the immune system

Publication Title

Induction of anergic or regulatory tumor-specific CD4<sup>+</sup> T cells in the tumor-draining lymph node.

Sample Metadata Fields

Time

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accession-icon GSE113625
Gene expression profile of chronically activated CD4+ T cells from cancer patients
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

CD4+ T cells as mediators of antitumor responses are beginning to be appreciated. Our team demonstrated that chronically activated CD4+ T cells (chCD4+ T cells) were expanded in the blood of cancer patients and their expansion is correlated with tumor regression.

Publication Title

Induction of anergic or regulatory tumor-specific CD4<sup>+</sup> T cells in the tumor-draining lymph node.

Sample Metadata Fields

Disease

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accession-icon SRP194595
Single-cell RNA-Seq Investigation of Foveal and Peripheral Expression in the Human Retina
  • organism-icon Homo sapiens
  • sample-icon 95 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Purpose: Single-cell RNA sequencing has revolutionized cell-type specific gene expression analysis. The goals of this study are to compare cell specific gene expression patterns between retinal cell types originating from the fovea and the periphery of human eyes. Methods: Independent libraries were prepared for foveal and peripheral samples of neural retina from three donors using the 10x Chromium system. Libraries were sequenced on a HiSeq4000. Sequenced reads were mapped to the human genome build hg19 will CellRanger(v3.0.1) and filters removed cells likely to be doublets or cells with a high proportion of mitochondrial reads. Clustering of cells with similar expression profiles was performed with Seurat (v2.3.4). Results: Independent libraries were prepared for foveal and peripheral samples of neural retina from three donors using the 10x Chromium system. Libraries were sequenced on a HiSeq4000. Sequenced reads were mapped to the human genome build hg19 will CellRanger(v3.0.1) and filters removed cells likely to be doublets or cells with a high proportion of mitochondrial reads. Clustering of cells with similar expression profiles was performed with Seurat (v2.3.4). Conclusions: Our study generates a large atlas of human retinal transcriptomes at the single cell level. We identified the majority of expected neural and supportive cell types, and describe regional differences in gene expression between the fovea and the periphery. Our results show that that single-cell RNA sequencing can be performed on human retina after cryopreservation, and that cone photoreceptors and Muller cells demonstrate region-specific patterns of gene expression. Overall design: mRNA profiles for thousands of cells from foveal and peripheral retinal isolates were generated from three human donor eyes using 10X Genomics Chromium single-cell system followed by sequencing on an Illumina HiSeq 4000.

Publication Title

Molecular characterization of foveal versus peripheral human retina by single-cell RNA sequencing.

Sample Metadata Fields

Subject

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accession-icon GSE39042
Expression data from MDA-MB-231 cells exposed to hypoxia and/or paclitaxel or epirubicin
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Hypoxia protects cancer cells from chemotherapeutic drug-induced cell death.

Publication Title

TMEM45A is essential for hypoxia-induced chemoresistance in breast and liver cancer cells.

Sample Metadata Fields

Cell line

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accession-icon SRP152577
PyMINEr Finds Gene and Autocrine/Paracrine Networks from Human Islet scRNAseq
  • organism-icon Homo sapiens
  • sample-icon 162 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Toolsets available for in-depth analysis of scRNAseq datasets by biologists with little informatics experience is limited. Here we describe an informatics tool (PyMINEr) that fully automates cell type identification, cell type-specific pathway analyses, graph theory-based analysis of gene regulation, and detection of autocrine/paracrine signaling networks in silico. We applied PyMINEr to interrogate human pancreatic islet scRNAseq datasets and discovered several features of co-expression graphs including: concordance of scRNAseq-graph structure with both protein-protein interactions and 3D-genomic architecture; association of high connectivity and low expression genes with cell type-enrichment; and potential for graph-structure to clarify potential etiologies of enigmatic disease-associated variants. We further created a consensus co-expression network and autocrine/paracrine signaling networks within and across islet cell types from 7-datasets. PyMINEr correctly identified changes in BMP/WNT signaling associated with cystic fibrosis pancreatic acinar-cell loss. This proof-of-principle study demonstrates that the PyMINEr framework will be a valuable resource for scRNAseq analyses. Overall design: Human islets were obtained from the integrated islet distribution program (IIDP), cultured overnight, then prepared for scRNAseq via the Fluidigm C1 platform. RNAseq was perfromed on Illumina HiSeq 2500.

Publication Title

PyMINEr Finds Gene and Autocrine-Paracrine Networks from Human Islet scRNA-Seq.

Sample Metadata Fields

Sex, Age, Specimen part, Race, Subject

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...

refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Developed by the Childhood Cancer Data Lab

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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