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accession-icon GSE32955
Gene expression profiles of T cell fraction enriched for donor antigen-reactive T cells in skin allografted recipient mice
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

No associated publication

Alternate Accession IDs

E-GEOD-32955

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE32952
Gene expression profiles of T cell fraction enriched for donor antigen-reactive T cells in skin allografted recipient mice (I)
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

Measurement of specific gene expression in clinical samples is a promising approach for monitoring the recipient immune status to the graft in organ transplantation. Identification of biomarker genes closely associated with tolerance or rejection is critical for this monitoring protocol. Unlike previous studies, our microarray analysis focused on donor antigen-reactive T cells, which were prepared by collecting CD69+ T cells from cocultures of recipient peripheral T cells and donor antigen-presenting cells. A comparison of different recipient groups enabled us to identify several tolerance- and rejection-correlated biomarker genes, including previously unknown genes. By measuring biomarker gene expression in the CD69+ T cell fraction using quantitative reverse-transcription polymerase chain reaction, we were able to precisely detect the immune status of recipients relative to their graft.

Publication Title

No associated publication

Alternate Accession IDs

E-GEOD-32952

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE32953
Gene expression profiles of T cell fraction enriched for donor antigen-reactive T cells in skin allografted recipient mice (II)
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

Measurement of specific gene expression in clinical samples is a promising approach for monitoring the recipient immune status to the graft in organ transplantation. Identification of biomarker genes closely associated with tolerance or rejection is critical for this monitoring protocol. Unlike previous studies, our microarray analysis focused on donor antigen-reactive T cells, which were prepared by collecting CD69+ T cells from cocultures of recipient peripheral T cells and donor antigen-presenting cells. A comparison of different recipient groups enabled us to identify several tolerance- and rejection-correlated biomarker genes, including previously unknown genes. By measuring biomarker gene expression in the CD69+ T cell fraction using quantitative reverse-transcription polymerase chain reaction, we were able to precisely detect the immune status of recipients relative to their graft.

Publication Title

No associated publication

Alternate Accession IDs

E-GEOD-32953

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE11677
Gene expression profiles of age-associated clonal expansions of CD8 memory T cells
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Many aged individuals develop monoclonal expansions of CD8 T cells. These expansions are derived from a CD8 memory T cell that outcompetes neighboring CD8 T cells. The molecular alterations within clonal expansions that confer this competitive advantage relative to other CD8 T cells remains unknown. These microarray experiments were designed to identify genes differentially expressed in age-associated expansions of CD8 memory T cells relative to polyclonal CD8 memory T cells found in the same aged mice.

Publication Title

Identification of two major types of age-associated CD8 clonal expansions with highly divergent properties.

Alternate Accession IDs

E-GEOD-11677

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE31210
Gene expression data for pathological stage I-II lung adenocarcinomas
  • organism-icon Homo sapiens
  • sample-icon 230 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Identification of genes up-regulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas.

Publication Title

Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas.

Alternate Accession IDs

E-GEOD-31210

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE35784
Gene expression profile of pediatric AML
  • organism-icon Homo sapiens
  • sample-icon 130 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gene expression data were obtained from 130 pediatric AML patients who were enrolled on the AML99 study conducted by the Japanese Childhood AML Cooperative Study Group.

Publication Title

No associated publication

Alternate Accession IDs

E-GEOD-35784

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE20196
Gene expression profile of poorly differentiated synovial sarcoma
  • organism-icon Homo sapiens
  • sample-icon 34 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Poorly differentiated type synovial sarcoma (PDSS) is a variant of synovial sarcoma characterized by predominantly round or short-spindled cells. Although accumulating evidence from clinicopathological studies suggests a strong association between this variant of synovial sarcoma and poor prognosis, little has been reported on the molecular basis of PDSS. To gain insight into the mechanism(s) that underlie the emergence of PDSS, we analyzed the gene expression profiles of 34 synovial sarcoma clinical samples, including 5 cases of PDSS, using an oligonucleotide microarray. In an unsupervised analysis, the 34 samples fell into 3 groups that correlated highly with histological subtype, namely, monophasic, biphasic, and poorly differentiated types. PDSS was characterized by down-regulation of genes associated with neuronal and skeletal development and cell adhesion, and up-regulation of genes on a specific chromosomal locus, 8q21.11. This locus-specific transcriptional activation in PDSS was confirmed by reverse transcriptase (RT)-PCR analysis of 9 additional synovial sarcoma samples. Our results indicate that PDSS tumors constitute a distinct genetic group based on expression profiles.

Publication Title

Gene expression profiling of synovial sarcoma: distinct signature of poorly differentiated type.

Alternate Accession IDs

E-GEOD-20196

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE14827
Gene expression profiles from osteosarcpma samples
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Osteosarcoma patients with development of pulmonary metastasis have still poorer prognosis in spite of aggressive treatment. However, molecular mechanism of metastasis is still unknown.

Publication Title

Reduced argininosuccinate synthetase is a predictive biomarker for the development of pulmonary metastasis in patients with osteosarcoma.

Alternate Accession IDs

E-GEOD-14827

Sample Metadata Fields

Sex, Age

View Samples
accession-icon GSE28284
Effects of genome architecture and epigenetic factors on susceptibility of promoter CpG islands to aberrant DNA methylation induction.
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Aberrant DNA methylation is induced at specific promoter CpG islands (CGIs) in contrast with mutations. The specificity is influenced by genome architecture and epigenetic factors, but their relationship is still unknown. In this study, we isolated promoter CGIs susceptible and resistant to aberrant methylation induction during prostate and breast carcinogenesis. The effect of genome architecture was more evident for promoter CGIs susceptible in both of the two tissues than for promoter CGIs susceptible only in one tissue. Multivariate analysis of promoter CGIs with tissue-nonspecific susceptibility showed that genome architecture, namely a remote location from SINE (OR=5.98; 95% CI=2.33-15.34) and from LINE (OR=2.08; 95% CI=1.03-4.21), was associated with increased susceptibility, independent of epigenetic factors such as the presence of RNA polymerase II (OR=0.09; 95% CI=0.02-0.48) and H3K27me3 (OR=3.28; 95% CI=1.17-9.21). These results showed that methylation susceptibility of promoter CGIs is determined both by genome architecture and epigenetic factors, independently.

Publication Title

Effects of genome architecture and epigenetic factors on susceptibility of promoter CpG islands to aberrant DNA methylation induction.

Alternate Accession IDs

E-GEOD-28284

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE27787
Hematopoietic cells and stem cells
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Forced expression of the histone demethylase Fbxl10 maintains self-renewing hematopoietic stem cells.

Alternate Accession IDs

E-GEOD-27787

Sample Metadata Fields

Specimen part

View Samples
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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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