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accession-icon GSE38642
Expression data from human pancreatic islets
  • organism-icon Homo sapiens
  • sample-icon 63 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Close to 50 genetic loci have been associated with type 2 diabetes (T2D), but they explain only 15% of the heritability.

Publication Title

A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE68853
Identification of proliferative and mature -cells in the islet of Langerhans
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Insulin-dependent diabetes is a complex multifactorial disorder characterized by

Publication Title

Identification of proliferative and mature β-cells in the islets of Langerhans.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE23310
Uncovering Genes and Regulatory Pathways Related to Urinary Albumin Excretion in Mice
  • organism-icon Mus musculus
  • sample-icon 173 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Identifying the genes underlying quantitative trait loci (QTL) for disease has proven difficult, mainly due to the low resolution of the approach and the complex genetics involved. However, recent advances in bioinformatics and the availability of genetic resources now make it possible to narrow the genetic intervals and test candidate genes. In addition to identifying the causative genes, defining the pathways that are affected by these QTL is of major importance as it can give us insight into the disease process and provide evidence to support candidate genes. In this study we mapped three significant and one suggestive QTL on Chromosomes (Chrs) 1, 4, 15, and 17, respectively, for increased albumin excretion (measured as albumin-to-creatinine ratio) in a cross between the MRL/MpJ and SM/J mouse inbred strains. By combining data from several sources and by utilizing gene expression data, we identified Tlr12 as a likely candidate for the Chr 4 QTL. Through the mapping of 33,881 transcripts measured by microarray on kidney RNA from each of the 173 male F2 animals, we identified several downstream pathways associated with these QTL. Among these were the glycan degradation, leukocyte migration, and antigen presenting pathways. We demonstrate that by combining data from multiple sources, we can identify not only genes that are likely to be causal candidates for QTL, but also the pathways through which these genes act to alter phenotypes. This combined approach provides valuable insights into the causes and consequences of renal disease.

Publication Title

Uncovering genes and regulatory pathways related to urinary albumin excretion.

Sample Metadata Fields

Sex, Age

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accession-icon SRP175072
Safety profiling of genetically engineered Pim-1 kinase overexpression for oncogenicity risk in human c-kit+ cardiac interstitial cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Bulk RNA-seq to profile of c-kit+ cardiac interstitial cells, comparing the transcriptomes of Pim-1 enhanced cardiac progenitor cells and transfection control Overall design: Transcriptional profiling of Pim-1 enhanced human derived cardiac interstitial cells by bulk RNA-Seq

Publication Title

Safety profiling of genetically engineered Pim-1 kinase overexpression for oncogenicity risk in human c-kit+ cardiac interstitial cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE65461
Transcriptome changes following loss of Apc in the intestine
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Nearly all colorectal cancers have dysregulated Wnt signalling, predominantly through the mutation of the Apc (Adenomatous Polyposis Coli) gene. Therefore it is of vital importance to elucidate the key Wnt target genes in intestinal cells in vivo. We have used a novel inducible cre-lox based murine system (designated ApcFlox) to investigate the consequences of perturbation of Wnt signalling following inactivation of Apc in vivo within 100% of the intestinal epithelium. We have employed microarray analysis at 3 time points within our ApcFlox system (Day 3 prior to the onset of phenotype, day 4 the establishment of the phenotype and day 5 gross phenotype of altered proliferation, differentiation and migration) and from adenomas arising in the ApcMin/+ background allowing us characterise Wnt/beta-catenin target genes based on their expression profiles during different stages of intestinal tumourigenesis. Furthermore, we have employed microarray analysis using livers from our ApcFlox system and have demonstrated that there is very little overlap in the Wnt target genes induced by Apc loss in the liver and the intestine. More importantly, we have been able to determine a novel set of putative Wnt/beta-catenin target genes which are upregulated at both early and late stages of tumourigenesis in the intestine and may represent novel therapeutic targets in colon cancer.

Publication Title

Hunk/Mak-v is a negative regulator of intestinal cell proliferation.

Sample Metadata Fields

Specimen part

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accession-icon GSE84392
Comparison between Nestin+ and Nestin- Ptch1 deficient GNPs
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The intermediate filament protein Nestin serves as a biomarker for stem cells and has been used to identify subsets of cancer stem-like cells. However, the mechanistic contributions of Nestin to cancer pathogenesis are not understood. Here we report that Nestin binds the hedgehog pathway transcription factor Gli3 to mediate the development of medulloblastomas of the hedgehog subtype. In a mouse model system, Nestin levels increased progressively during medulloblastoma formation resulting in enhanced tumor growth. Conversely, loss of Nestin dramatically inhibited proliferation and promoted differentiation. Mechanistic investigations revealed that the tumor-promoting effects of Nestin were mediated by binding to Gli3, a zinc finger transcription factor that negatively regulates hedgehog signaling. Nestin binding to Gli3 blocked Gli3 phosphorylation and its subsequent proteolytic processing, thereby abrogating its ability to negatively regulate the hedgehog pathway. Our findings show how Nestin drives hedgehog pathway-driven cancers and uncover in Gli3 a therapeutic target to treat these malignancies.

Publication Title

Nestin Mediates Hedgehog Pathway Tumorigenesis.

Sample Metadata Fields

Specimen part

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accession-icon GSE41410
Co-expression of genes with ERG in prostate cancers and cell lines
  • organism-icon Homo sapiens
  • sample-icon 65 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Identification of TDRD1 as a direct target gene of ERG in primary prostate cancer.

Sample Metadata Fields

Cell line

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accession-icon GSE41408
Co-expression of genes with ERG in prostate cancers
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

ERG overexpression is the most frequent molecular alteration in prostate cancer. We analyzed different stages of prostate cancer to identify genes that were coexpressed with ERG overexpression. In primary prostate tumors, it was shown that TDRD1 expression was the strongest correlated gene with ERG overexpression and we suggest TDRD1 as a direct ERG target gene.

Publication Title

Identification of TDRD1 as a direct target gene of ERG in primary prostate cancer.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE41407
Co-expression of genes with ERG in prostate cancer cell lines
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

ERG overexpression is the most frequent molecular alteration in prostate cancer. We analyzed different stages of prostate cancer to identify genes that were coexpressed with ERG overexpression. In primary prostate tumors, it was shown that TDRD1 expression was the strongest correlated gene with ERG overexpression and we suggest TDRD1 as a direct ERG target gene.

Publication Title

Identification of TDRD1 as a direct target gene of ERG in primary prostate cancer.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE40393
Gene x environment effect of serotonin transporter genotype and acute stressor on amygdala gene expression
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The amygdala is a prominent region of the brain processing stress-related emotion and vigilance. Additionally it is known that the serotonergic system is strongly involved in stress response and adaptation. The serotonin transporter (5-HTT) as key regulator of serotonergic activity in the brain is associated with stress-related neuropsychiatric disorders as well as heightened trait anxiety/dysphoria and exaggerated response to fear and environmental stress in humans. Also 5-HTT knockout mice display increased anxiety- and depression-related behaviors, altered stress reactivity and stress-coping abilities, gene expression differences and altered dendritic morphology.

Publication Title

Effect of acute stressor and serotonin transporter genotype on amygdala first wave transcriptome in mice.

Sample Metadata Fields

Sex, Specimen part, Treatment

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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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