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accession-icon SRP154939
Whole mesenteric lymph nodes (mLN) RNA-seq from MNV or Reovirus infected C57BL/6 mice
  • organism-icon Mus musculus
  • sample-icon 25 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

mRNA profiles of 8 weeks old C57BL/6 mice 2 days after infections with 5e7 pfu of various strains of murine norovirus (MNV) or 1e8 pfu of T1L reovirus were evauated Overall design: mRNA profiles of 8 weeks old C57BL/6 mice 2 days after infections with 5e7 pfu of various strains of murine norovirus (MNV) or 1e8 pfu of T1L reovirus were evauated

Publication Title

Murine Norovirus Infection Induces T<sub>H</sub>1 Inflammatory Responses to Dietary Antigens.

Sample Metadata Fields

Age, Specimen part, Cell line, Subject

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accession-icon GSE7491
Expression data from rat lung alveolar development
  • organism-icon Rattus norvegicus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Lung alveolarization is a complex process that involves interactions between several cell types and leads to considerable increase in gas-exchange surface area. The step designated secondary septation includes elastogenesis from interstitial fibroblasts.

Publication Title

Gene expression profiling in lung fibroblasts reveals new players in alveolarization.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE102067
An RNAi screen reveals an essential role for HIPK4 in human skin epithelial differentiation from iPSCs
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Molecular mechanisms that are responsible for the development of human skin epithelial cells are not completely understood so far. As a consequence, the efficiency to establish a pure skin epithelial cell population from human induced pluripotent stem cells (hiPSC) remains poor. Using an approach including RNA interference and high-throughput imaging of early epithelial cells, we could identify candidate kinases which are involved in skin epithelial differentiation. Among them, we found HIPK4 to be an important inhibitor of this process. Indeed, its silencing increased the amount of generated skin epithelial precursors, increased the amount of generated keratinocytes and improved growth and differentiation of organotypic cultures, allowing for the formation of a denser basal layer and stratification with the expression of several keratins. Our data bring substantial input in the regulation of human skin epithelial differentiation and for improving differentiation protocols from pluripotent stem cells.

Publication Title

An RNAi Screen Reveals an Essential Role for HIPK4 in Human Skin Epithelial Differentiation from iPSCs.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE11358
Histones associated with downregulated genes are hypo-acetylated in Huntingtons disease models
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Transcriptional dysregulation plays a major role in the pathology of Huntington's disease (HD). However, the mechanisms causing selective downregulation of genes remain unknown. Histones regulate chromatin structure and thereby control gene expression; recent studies have demonstrated a therapeutic role for histone deacetylase (HDAC) inhibitors in polyglutamine diseases. This study demonstrates that despite no change in overall acetylated histone levels, histone H3 is hypo-acetylated at promoters of downregulated genes in R6/2 mice, ST14a and STHdh cells, as demonstrated by in vivo chromatin immunoprecipitation. In addition, HDAC inhibitor treatment increases association of acetylated histones with downregulated genes and corrects mRNA abnormalities. In contrast, there is a decrease in mRNA levels in wild-type cells following treatment with a histone acetyltransferase inhibitor. Although changes in histone acetylation correlate with decreased gene expression, histone hypo-acetylation may be a late event, as no hypo-acetylation is observed in 4-week-old R6/2 mice. Nevertheless, treatment with HDAC inhibitors corrects mRNA abnormalities through modification of histone proteins and may prove to be of therapeutic value in HD.

Publication Title

Histones associated with downregulated genes are hypo-acetylated in Huntington's disease models.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP186927
AmpliSeq transcriptome profiling of human adipose tissue progenitor cell types
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Three different progenitor cell subsets in subcutaneous and visceral adipose tissues derived from 5 obese patients were subjected to AmpliSeq transcriptome profiling. Transcriptomic profiles were analyzed to compare progenitor cell subsets and the impact of subcutaneous and visceral adipose tissue location. Overall design: Transcriptomic profiling of 3 different progenitor cell types in subcutaneous and visceral adipose tissues derived from 5 obese patients (3X2X5=30 samples).

Publication Title

Lobular architecture of human adipose tissue defines the niche and fate of progenitor cells.

Sample Metadata Fields

Subject

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accession-icon GSE30292
Establishment of objective criteria for selecting relevant intestinal cell-based models
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The objective of this study was to make use of gene expression signatures and functional assays to delineate differences between various intestinal colon carcinoma cell lines and normal intestinal epithelium to assess their appropriateness as a tumor model or for drug absorption studies.

Publication Title

Defining new criteria for selection of cell-based intestinal models using publicly available databases.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE137110
Chronic mucocutaneous candidiasis and connective tissue disorder in humans with impaired JNK1-dependent responses to IL-17A/F and TGF-?
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Chronic mucocutaneous candidiasis and connective tissue disorder in humans with impaired JNK1-dependent responses to IL-17A/F and TGF-β.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment, Time

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accession-icon GSE16458
A simple method to integrate different versions of Affymetrix microarrays using duplicate samples
  • organism-icon Rattus norvegicus
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

The size and scope of microarray experiments continue to increase. However, datasets generated on different platforms or at different centres contain biases. Improved techniques are needed to remove platform- and batch-specific biases. One experimental control is the replicate hybridization of a subset of samples at each site or on each platform to learn the relationship between the two platforms. To date, no algorithm exists to specifically use this type of control. LTR is a linear-modelling-based algorithm that learns the relationship between different microarray batches from replicate hybridizations. LTR was tested on a new benchmark dataset of 20 samples hybridized to different Affymetrix microarray platforms. Before LTR, the two platforms were significantly different; application of LTR removed this bias. LTR was tested with six separate data pre-processing algorithms, and its effectiveness was independent of the pre-processing algorithm. Sample-size experiments indicate that just three replicate hybridizations can significantly reduce bias. An R library implementing LTR is available.

Publication Title

LTR: Linear Cross-Platform Integration of Microarray Data.

Sample Metadata Fields

Sex

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accession-icon GSE73599
Celiac disease T cell clone response to CD3/CD28 stimulation
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To identify the CD4+ T cell cytokines responsible for the proliferation of the Lin-IEL lines CD4+ T cell clone L10, which recognises DQ2-glia-1, one of the immunodominant T cell epitopes in celiac disease, was stimulated for 3 hours in IMDM with plate-bound CD3/CD28-specific (2.5 g/ml each) or control antibodies coated onto 6-well non-tissue culture treated plates. Three independent biological replicates were performed, each time including 6 million Ficoll-purified live cells per condition. RNA was purified from these cells using the RNAeasy mini kit (Qiagen, Venlo, the Netherlands). cDNA was amplified using the Applause WT-Amp system (NuGEN technologies, Bemmel, the Netherlands) and biotin-labelled with the Encore Biotin Module (NuGEN). Human Gene 1.0 ST arrays (Affymetrix, High Wycombe, UK) were employed to quantify global gene expression.

Publication Title

CD4 T-cell cytokines synergize to induce proliferation of malignant and nonmalignant innate intraepithelial lymphocytes.

Sample Metadata Fields

Specimen part

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accession-icon GSE70421
SMARCB1-deficient rhaboid tumors of the kidney and renal medullary carcinomas.
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to compared gene expression profilings in various tumors of the kidney.

Publication Title

Balanced Translocations Disrupting SMARCB1 Are Hallmark Recurrent Genetic Alterations in Renal Medullary Carcinomas.

Sample Metadata Fields

Specimen part

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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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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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