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accession-icon GSE9006
Gene expression in PBMCs from children with diabetes
  • organism-icon Homo sapiens
  • sample-icon 224 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Objective: We hypothesized that type 1 diabetes (T1D) is accompanied by changes in gene expression in peripheral blood mononuclear cells (PBMCs) due to dysregulation of adaptive and innate immunity, counterregulatory responses to immune dysregulation, insulin deficiency and hyperglycemia. Research Design and Methods: Microarray analysis was performed on PBMCs from 43 patients with newly diagnosed T1D, 12 patients with newly diagnosed type 2 diabetes (T2D) and 24 healthy controls. One and four month follow-up samples were obtained from 20 of the T1D patients.

Publication Title

Gene expression in peripheral blood mononuclear cells from children with diabetes.

Sample Metadata Fields

Sex, Age, Treatment, Race

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accession-icon GSE29536
Whole Blood Transcriptional Modules generated on Illumina Hu-6 V2 Beadchips
  • organism-icon Homo sapiens
  • sample-icon 410 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

This dataset was used to establish whole blood transcriptional modules (n=260) that represent groups of coordinately expressed transcripts that exhibit altered abundance within individual datasets or across multiple datasets. This modular framework was generated to reduce the dimensionality of whole blood microarray data processed on the Illumina Beadchip platform yielding data-driven transcriptional modules with biologic meaning.

Publication Title

Interferon signature in the blood in inflammatory common variable immune deficiency.

Sample Metadata Fields

Disease

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accession-icon GSE13015
Genomic Transcriptional Profiling Identifies a Blood Biomarker Signature for the Diagnosis of Septicemic Melioidosis
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge IconSentrix Human-6 v2 Expression BeadChip

Description

Melioidosis is a severe infectious disease caused by Burkholderia pseudomallei, a gram-negative bacillus classified by the NIAID as a category B priority agent. Septicemia is the most common presentation of the disease with 40% mortality rate even with appropriate treatments. Faster diagnostic procedures are required to improve therapeutic response and survival rates. We have used microarray technology to generate genome-wide transcriptional profiles (>48,000 transcripts) of whole blood obtained from patients with septicemic melioidosis (n=32), patients with sepsis caused by other pathogens (n=31), and uninfected controls (n=29). Unsupervised analyses demonstrated the existence of a whole blood transcriptional signature distinguishing patients with sepsis from control subjects. The majority of changes observed were common to both septicemic melioidosis and sepsis caused by other infections, including genes related to inflammation, interferon-related genes, neutrophils, cytotoxic cells, and T cells. Finally, class prediction analysis identified a 37 transcript candidate diagnostic signature that distinguished melioidosis from sepsis caused by other organisms with 100% and 78% accuracy in training and independent test sets, respectively. This finding was confirmed by the independent validation set, which showed 80% prediction accuracy. This signature was highly enriched in genes coding for products involved in the MHC Class II antigen processing and presentation pathway. Transcriptional patterns of whole blood RNA distinguish patients with septicemic melioidosis from patients with sepsis caused by other pathogens. Once confirmed in a large scale trial this diagnostic signature might constitute the basis of a differential diagnostic assay.

Publication Title

Genomic transcriptional profiling identifies a candidate blood biomarker signature for the diagnosis of septicemic melioidosis.

Sample Metadata Fields

Sex, Age, Treatment, Race

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accession-icon GSE13151
Differential roles of ROR gamma-t in the development of NKp46+ spleen (LTIL) cells and NKp46+ NK cells in gut and skin
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon (lluminamouse6v1.1expressionbeadchip[arrayaddressidversion)

Description

Natural killer (NK) cells are NKp46+CD3- lymphocytes that can perform granule-dependent cytotoxicity and produce interferon-gamma, when isolated from blood, lymphoid organs, lung, liver and uterus. Here we identify in dermis, gut lamina propria and cryptopatches, very distinct populations of NKp46+CD3- cells with reduced ability to degranulate and to produce interferon-gamma. In gut, the transcription factor RORgamma-t and CD127 (IL-7R alpha) defined a novel subset of NKp46+CD3- that is reminiscent of lymphoid tissue inducer (LTi)-like cells. Gut ROR gamma t+NKp46+ cells produced IL-22 in contrast to ROR-gamma t-independent lamina propria and dermis NK cells. These data show that LTi-like cells and NK cells share unanticipated similarities and reveal the heterogeneity of NKp46+CD3- cells in innate immunity, lymphoid organization and local tissue repair.

Publication Title

Influence of the transcription factor RORgammat on the development of NKp46+ cell populations in gut and skin.

Sample Metadata Fields

Sex, Age

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accession-icon GSE32140
The response of PBMCs and primary airway epithelial cells to Influenza and RSV virus
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 99 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Plasticity and virus specificity of the airway epithelial cell immune response during respiratory virus infection.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE34205
Transcriptional profile of PBMCs in patients with acute RSV or Influenza infection
  • organism-icon Homo sapiens
  • sample-icon 99 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To study the transcriptional profile of patients with acute RSV or Influenza infection,children of median age 2.4 months (range 1.5-8.6) hospitalized with acute RSV and influenza virus infection were offered study enrollment after microbiologic confirmation of the diagnosis. Blood samples were collected from them within 42-72 hours of hospitalization. We excluded children with suspected or proven polymicrobial infections, with underlying chronic medical conditions (i.e congenital heart disease, renal insufficiency), with immunodeficiency, or those who received systemic steroids or other immunomodulatory therapies. The RSV cohort consisted of 51 patients with median age of 2 months (range 1.5-3.9) and the influenza cohort had 28 patients with median age of 5.5 months (range 1.4-21). Control samples were obtained from healthy children undergoing elective surgical procedures or at outpatient clinic visits. To exclude viral co-infections we performed nasopharyngeal viral cultures of all subjects. We recruited 10 control patients for the RSV cohort with median age of 6.7 months (range 5-10), and 12 control patients for the influenza cohort with median age of18.5 months (range 10.5-26).

Publication Title

Plasticity and virus specificity of the airway epithelial cell immune response during respiratory virus infection.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE29333
Genome-wide analysis of gene expression profiles in individuals infected with the Human T-Lymphotropic virus Type 1 (HTLV-1)
  • organism-icon Homo sapiens
  • sample-icon 49 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Systems biology approaches reveal a specific interferon-inducible signature in HTLV-1 associated myelopathy.

Sample Metadata Fields

Sex, Age, Disease, Race

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accession-icon GSE29312
Genome-wide analysis of gene expression profiles in individuals infected with the Human T-Lymphotropic virus Type 1 (HTLV-1) - train set
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

Infection with the human T lymphotropic virus type 1 (HTLV-1) remains asymptomatic in the majority of carriers; however, some 5% develop a chronic inflammation of the central nervous system termed HTLV-1-associated myelopathy (HAM). It is not well understood how the virus triggers the onset of HAM after many years of clinical latency and importantly, what distinguishes hosts who develop the disease from those who remain asymptomatic. In this study we tested the hypothesis that patients with HAM can be distinguished from asymptomatic HTLV-1 carriers (ACs) and uninfected subjects by their whole blood transcriptional profiles. Here, we compare unstimulated whole blood gene expression profiles of 20 asymptomatic HTLV-1 carriers (ACs), 10 patients with HAM and 9 uninfected healthy control subjects to (1) identify a transcriptional signature associated with presence of HAM and (2) identify cell types and pathways abnormally regulated in HAM by canonical and modular pathway analysis.

Publication Title

Systems biology approaches reveal a specific interferon-inducible signature in HTLV-1 associated myelopathy.

Sample Metadata Fields

Sex, Age, Disease, Race

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accession-icon GSE29332
Genome-wide analysis of gene expression profiles in individuals infected with the Human T-Lymphotropic virus Type 1 (HTLV-1) - test set
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

Infection with the human T lymphotropic virus type 1 (HTLV-1) remains asymptomatic in the majority of carriers; however, some 5% develop a chronic inflammation of the central nervous system termed HTLV-1-associated myelopathy (HAM). It is not well understood how the virus triggers the onset of HAM after many years of clinical latency and importantly, what distinguishes hosts who develop the disease from those who remain asymptomatic. In a previous study we identified a 80-gene transcriptional signature of HAM based in the hypothesis that patients with HAM can be distinguished from asymptomatic HTLV-1 carriers (ACs) and uninfected subjects by their whole blood transcriptional profiles. In this study we wished to validate the 80-gene signature on an independent cohort comprising 17 asymptomatic HTLV-1 carriers (ACs), 10 patients with HAM and 8 uninfected healthy control subjects.

Publication Title

Systems biology approaches reveal a specific interferon-inducible signature in HTLV-1 associated myelopathy.

Sample Metadata Fields

Sex, Age, Disease, Race

View Samples
accession-icon GSE6222
Genome-wide analysis of gene expression patterns in human liver cancers
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To investigate the mechanisms of liver cancer progression and metastasis, we did expression profiling of human liver cancer and benign tissues.

Publication Title

Identification of SOX4 target genes using phylogenetic footprinting-based prediction from expression microarrays suggests that overexpression of SOX4 potentiates metastasis in hepatocellular carcinoma.

Sample Metadata Fields

No sample metadata fields

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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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