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accession-icon GSE47185
In silico nano-dissection: defining cell type specificity at transcriptional level in human disease
  • organism-icon Homo sapiens
  • sample-icon 220 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

Defining cell-type specificity at the transcriptional level in human disease.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE47183
In silico nano-dissection: defining cell type specificity at transcriptional level in human disease (glomeruli)
  • organism-icon Homo sapiens
  • sample-icon 114 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To identify genes with cell-lineage-specific expression not accessible by experimental micro-dissection, we developed a genome-scale iterative method, in-silico nano-dissection, which leverages high-throughput functional-genomics data from tissue homogenates using a machine-learning framework.

Publication Title

Defining cell-type specificity at the transcriptional level in human disease.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE47184
In silico nano-dissection: defining cell type specificity at transcriptional level in human disease (tubulointerstitium)
  • organism-icon Homo sapiens
  • sample-icon 106 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To identify genes with cell-lineage-specific expression not accessible by experimental micro-dissection, we developed a genome-scale iterative method, in-silico nano-dissection, which leverages high-throughput functional-genomics data from tissue homogenates using a machine-learning framework.

Publication Title

Defining cell-type specificity at the transcriptional level in human disease.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE28976
Expression data from human breast cancer cell lines after demethylation treatment
  • organism-icon Homo sapiens
  • sample-icon 39 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

Integrated epigenetics of human breast cancer: synoptic investigation of targeted genes, microRNAs and proteins upon demethylation treatment.

Sample Metadata Fields

Treatment

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accession-icon GSE28968
MRNA expression data from human breast cancer cell lines after demethylation treatment.
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The contribution of aberrant DNA methylation and the downstream effects in tumorogenesis through silencing of tumor suppressor genes (TSGs) and microRNAs has been investigated. Since these epigenetic alterations can be reversed, we investigated the effects of the epigenetic therapy in breast cancer cell lines.

Publication Title

Integrated epigenetics of human breast cancer: synoptic investigation of targeted genes, microRNAs and proteins upon demethylation treatment.

Sample Metadata Fields

Treatment

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accession-icon GSE69438
Tissue Transcriptome Driven Identification of Epidermal Growth Factor as a Chronic Kidney Disease Biomarker
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We identified EGF as the top candidates predicting kidney function through an intrarenal transcriptome-driven approach, and demonstrated it is an independent risk predictor of CKD progression and can significantly improve prediction of renal outcome by established clinical parameters in diverse populations with CKD from a wide spectrum of causes and stages

Publication Title

Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE112453
Expression data from myeloid progenitors derived from control and antibiotic-treated wild-type C57BL/6 mice
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Myeloid progenitors derived from antibiotic-treated mice have cell-intrinsic functional defects. In this microarray dataset, the transcriptomes of bone marrow myeloid progenitors from antibiotic-treated and control mice are compared.

Publication Title

Microbiota-dependent signals are required to sustain TLR-mediated immune responses.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE43583
Genome wide gene expression in a patient with 15q13.3 homozygous microdeletion syndrome
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

We identified a novel homozygous 15q13.3 microdeletion in a young boy with a complex neurodevelopmental disorder characterized by severe cerebral visual impairment with additional signs of congenital stationary night blindness (CSNB), congenital hypotonia with areflexia, profound intellectual disability, and refractory epilepsy. The mechanisms by which the genes in the deleted region exert their effect are unclear. In this paper we probed the role of downstream effects of the deletions as a contributing mechanism to the molecular basis of the observed phenotype. We analyzed gene expression of lymphoblastoid cells derived from peripheral blood of the proband and his relatives to ascertain the relative effects of the homozygous and heterozygous deletions.

Publication Title

Genome-wide gene expression in a patient with 15q13.3 homozygous microdeletion syndrome.

Sample Metadata Fields

Cell line

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accession-icon GSE19154
Exon level integration of proteomics and microarray data
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Background: Previous studies comparing quantitative proteomics and microarray data have generally found poor correspondence between the two. We hypothesised that this might in part be because the different assays were targeting different parts of the expressed genome and might therefore be subjected to confounding effects from processes such as alternative splicing. Results: Using a genome database as a platform for integration, we combined quantitative protein mass spectrometry with Affymetrix Exon array data at the level of individual exons. We found significantly higher degrees of correlation than have been previously observed (r=0.808). The study was performed using cell lines in equilibrium in order to reduce a major potential source of biological variation, thus allowing the analysis to focus on the data integration methods in order to establish their performance. Conclusion: We conclude that much of the variation observed when integrating microarray and proteomics data may occur as a consequence both of the data analysis and of the high granularity to which studies have until recently been limited. The approach opens up the possibility for the first time of considering combined microarray and proteomics datasets at the level of individual exons and isoforms, important given the high proportion of alternative splicing observed in the human genome.

Publication Title

Exon level integration of proteomics and microarray data.

Sample Metadata Fields

Cell line

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accession-icon SRP014146
Molecular Rejuvenation of Gene Expression Pattern of Photoaged and Intrinsically Aged Human Skin by Broadband Light Treatment
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Studies in model organisms suggest that aged cells can be functionally rejuvenated, but whether this concept applies to human skin is unclear. Here we apply deep sequencing of RNA 3'' ends ("3-seq") to discover the gene expression program associated with human photoaging and intrinsic skin aging (collectively termed "skin aging") and the impact of broadband light (BBL) treatment. We find that skin aging was associated with the significantly altered expression level of 2,265 coding and noncoding RNAs, of which 1,293 became "rejuvenated" after BBL treatment, i.e. more similar in expression level of youthful skin. Rejuvenated genes (RGs) included several known key regulators of organismal longevity and their proximal long non-coding RNAs. Skin aging is not associated with systematic changes in 3'' end mRNA processing. Hence, BBL treatment can restore the gene expression pattern of photoaged and intrinsically aged human skin to resemble young skin. In addition, our data reveals a novel set of targets that may lead to new insights into the human skin aging process. Overall design: Examination of broadband light treated and untreated human skin transcriptomes of 5 women aged 50 years or more. They were compared to the skin transcriptomes of 5 young women aged 30 years or less.

Publication Title

Rejuvenation of gene expression pattern of aged human skin by broadband light treatment: a pilot study.

Sample Metadata Fields

Sex, Specimen part, Treatment, Subject

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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