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accession-icon GSE44555
Multiple tissue expression data from inbreds and F1 of CAST, PWK, and WSB
  • organism-icon Mus musculus
  • sample-icon 384 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

We create catalogues of genes showing significant strain, parent-of-origin, dominance, sex effect in inbreds and reciprocal F1 hybrids of three wild-derived strains (CAST, PWK, WSB) across 4 different tissues (brain, kidney, liver, and lung)

Publication Title

Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE67755
Chronic haloperidol effects on gene expression and chromatin accessibility in mouse brain
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Comparative genomic evidence for the involvement of schizophrenia risk genes in antipsychotic effects.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE67753
Chronic haloperidol effects on gene expression in mouse [array]
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

We evaluate the effects of chronic administration of antipsychotic haloperidol versus placebo in male, 8-week old, C57BL/6J mice.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE60690
Gene Expression in Transformed Lymphocytes Reveals Phenotype-Modifying Pathways in Cystic Fibrosis
  • organism-icon Homo sapiens
  • sample-icon 754 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Heritable genetic variants modify cystic fibrosis (CF) clinical phenotypes, e.g., lung disease, age-of-onset of persistent Pseudomonas aeruginosa (P. aeruginosa), and meconium ileus (MI). Previous genome wide association studies (GWAS) have begun to inform the genetic architecture of CF phenotypes. Analyses of gene expression will complement GWAS, as demonstrated by analyses of gene expression in lymphoblastoid cell lines (LCLs) to identify disease-related pathophysiological processes for non-CF complex traits. In this study, global gene expression was measured in RNA from LCLs from 754 CF patients and analyzed for association with lung disease severity, age-of-onset of persistent P. aeruginosa pulmonary infection, and MI at birth. Each phenotype displayed distinct expression associations. Most pathways significantly associated with lung disease were related to membranes, vesicle traffic, and Golgi/endoplasmic reticulum (ER). Pathways containing HLA genes (Class I and II) were significantly associated with both lung and P. aeruginosa phenotypes, but they displayed qualitative differences between phenotypes. MI associated with pathways involving oxidative phosphorylation. The results support the concept that gene expression associated with heritable variation acts to modify phenotypes in CF.

Publication Title

Gene expression in transformed lymphocytes reveals variation in endomembrane and HLA pathways modifying cystic fibrosis pulmonary phenotypes.

Sample Metadata Fields

Sex

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accession-icon GSE35571
Gene expression data from 131 human subjects in Detroit, Michigan
  • organism-icon Homo sapiens
  • sample-icon 131 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background

Publication Title

Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes.

Sample Metadata Fields

Sex, Disease

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accession-icon GSE10313
Identifying Novel Predictors of Resistance to DNA Damaging Agents
  • organism-icon Homo sapiens
  • sample-icon 98 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We have investigated whether gene expression signatures can be used to predict inter-individual responses to DNA damaging agents

Publication Title

Genomic predictors of interindividual differences in response to DNA damaging agents.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16059
Gene Expression in Peripheral Blood Leucocytes in Monozygotic Twins Discordant for Chronic Fatigue
  • organism-icon Homo sapiens
  • sample-icon 83 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background. Chronic fatiguing illness remains a poorly understood syndrome of unknown pathogenesis. We attempted to identify biomarkers for chronic fatiguing illness using microarrays to query the transcriptome in peripheral blood leukocytes. Methods. Cases were 44 individuals who were clinically evaluated and found to meet standard international criteria for chronic fatigue syndrome or idiopathic chronic fatigue, and controls were their monozygotic co-twins who were clinically evaluated and never had even one month of impairing fatigue. Biological sampling conditions were standardized and RNA stabilizing media were used. These methodological features provide rigorous control for bias resulting from case-control mismatched ancestry and experimental error. Individual gene expression profiles were assessed using Affymetrix Human Genome U133 Plus 2.0 arrays. Findings. There were no significant differences in gene expression for any transcript. Conclusions. Contrary to our expectations, we were unable to identify a biomarker for chronic fatiguing illness in the transcriptome of peripheral blood leukocytes suggesting that positive findings in prior studies may have resulted from experimental bias.

Publication Title

Gene expression in peripheral blood leukocytes in monozygotic twins discordant for chronic fatigue: no evidence of a biomarker.

Sample Metadata Fields

Sex

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accession-icon GSE47551
mRNA expression data from either wild-type mice or Scnn1b-transgenic mice at post-natal days 0, 3, 10, and 42
  • organism-icon Mus musculus
  • sample-icon 83 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st), Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene expression in whole lung and pulmonary macrophages reflects the dynamic pathology associated with airway surface dehydration.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE48355
Prenatal arsenic exposure and the epigenome
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconAgilent-031181 Unrestricted_Human_miRNA_V16.0_Microarray 030840 (Feature Number version), Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Prenatal arsenic exposure and the epigenome: altered microRNAs associated with innate and adaptive immune signaling in newborn cord blood.

Sample Metadata Fields

Specimen part

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accession-icon GSE73377
Epigenetics and Preeclampsia: Defining Functional Epimutations in the Preeclamptic Placenta Related to the TGF- Pathway
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st), Illumina HumanMethylation450 BeadChip (HumanMethylation450_15017482)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Epigenetics and Preeclampsia: Defining Functional Epimutations in the Preeclamptic Placenta Related to the TGF-β Pathway.

Sample Metadata Fields

Specimen part, Disease, Race

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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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