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accession-icon GSE104403
Expression data in Ucp2+/+ (WT) and Ucp2-/- (KO) colon tumors from AOM/DSS-treated mice
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The objective of the study was to evalute the changes in gene expression associated to UCP2 invalidation in colon tumors from AOM/DSS-treated mice

Publication Title

UCP2 Deficiency Increases Colon Tumorigenesis by Promoting Lipid Synthesis and Depleting NADPH for Antioxidant Defenses.

Sample Metadata Fields

Specimen part

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accession-icon GSE7676
Changes in gene expression following Protocadherin 12 knockout
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Protocadherin 12 (Pcdh12) is a transmembrane adhesive protein with homophilic adhesive properties and expressed in endothelial cells, the glycogen trophoblast cells of the placenta, and the mesangial cells of kidney glomeruli. Pcdh12-deficient mice are alive although they show alterations in placenta development.

Publication Title

Protocadherin 12 deficiency alters morphogenesis and transcriptional profile of the placenta.

Sample Metadata Fields

Sex

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accession-icon SRP053101
Impact of bariatric surgery on RNA-seq gene expression profiles of adipose tissue in humans
  • organism-icon Homo sapiens
  • sample-icon 88 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Bariatric surgery is the most effective therapy of severe human obesity. It is associated with improvements in metabolic and non metabolic co-morbidities which are thought to be mediated by a decrease of adipose tissue inflammation. However, the molecular mechanisms behind these beneficial effects are poorly understood. We analyzed expression profiles in subcutaneous adipose tissue from 22 obese women before and 3 months after surgery using the RNA-seq technology. Of 15,972 detected genes, 1214 were differentially expressed after surgery. Upregulated genes were mostly involved in the basal cellular machinery. Downregulated genes were enriched in metabolic functions of adipose tissue. At baseline, we identified 26 modules of coexpressed genes. The four most stable modules reflected the innate and adaptive immune responses of adipose tissue, including a general signature of innate immune cells, an adaptive immune response elicited by T lymphocytes, a neutrophil-mediated inflammatory signature and an interferon-signaling pathway, respectively. After surgery, a few crucial molecules involved in chemotaxis and activation of immune cells were disconnected from their respective networks. These molecules may represent therapeutic targets against adipose inflammation. Overall design: mRNA sequencing of subcutaneous adipose tissue (SAT) samples from 22 obese women before and 3 months after bariatric surgery

Publication Title

Bariatric Surgery Induces Disruption in Inflammatory Signaling Pathways Mediated by Immune Cells in Adipose Tissue: A RNA-Seq Study.

Sample Metadata Fields

No sample metadata fields

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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 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 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

View Samples
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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