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accession-icon GSE51717
Expression analysis of Reh cells after transfection with constitutively active variants of IRF5 (IRF5-4D) and/or constitutively active IKK(EE)
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Genome-wide gene expression analysis of Reh cells following transfection with constitutively active IRF5-4D, constitutively active IKK(EE), or both in combination.

Publication Title

Mapping of transcription factor motifs in active chromatin identifies IRF5 as key regulator in classical Hodgkin lymphoma.

Sample Metadata Fields

Cell line

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accession-icon GSE20115
Expression analysis of Reh cells after transfection with shRNA targeting CBFA2T3 and/or constitutively active IKK(EE)
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Genome-wide gene expression analysis of Reh cells following transfection with shRNA targeting CBFA2T3, constitutively active IKK(EE), or both in combination.

Publication Title

Derepression of an endogenous long terminal repeat activates the CSF1R proto-oncogene in human lymphoma.

Sample Metadata Fields

Cell line

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accession-icon GSE51719
Expression analysis of murine splenic B-cells after retroviral transduction with a constitutively active variant of IRF5 (IRF5-4D)
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 R2 expression beadchip

Description

Genome-wide gene expression analysis of murine splenic B-cells following retroviral transduction with a constitutively active IRF5 (IRF5-4D)

Publication Title

Mapping of transcription factor motifs in active chromatin identifies IRF5 as key regulator in classical Hodgkin lymphoma.

Sample Metadata Fields

Specimen part

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accession-icon GSE18679
TimEX from human embryonic stem cells, mesenchymal stem cells, and erythroid cells
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The organization of mammalian DNA replication is poorly understood. We have produced genome-wide high-resolution dynamic maps of the timing of replication in human erythroid, mesenchymal and embryonic stem cells using TimEX, a method that relies on gaussian convolution of massive, highly redundant determinations of DNA copy number variations during S phase obtained using either high-density oligonucleotide tiling arrays or massively-parallel sequencing to produce replication timing profiles. We show that in untransformed human cells, timing of replication is highly regulated and highly synchronous, and that many genomic segments are replicated in temporal transition regions devoid of initiation where replication forks progress unidirectionally from origins that can be hundreds of kilobases away. Absence of initiation in one transition region is shown at the molecular level by SMARD analysis. Comparison of ES and erythroid cells replication patterns revealed that these cells replicate about 20% of their genome in different quarter of S phase and that ES cells replicate a larger proportion of their genome in early S phase than erythroid cells. Importantly, we detected a strong inverse relationship between timing of replication and distance to the closest expressed gene. This relationship can be used to predict tissue specific timing of replication profiles from expression data and genomic annotations. We also provide evidence that early origins of replication are preferentially located near highly expressed genes, that mid firing origins are located near moderately expressed genes and that late firing origins are located far from genes.

Publication Title

Predictable dynamic program of timing of DNA replication in human cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE7491
Expression data from rat lung alveolar development
  • organism-icon Rattus norvegicus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Lung alveolarization is a complex process that involves interactions between several cell types and leads to considerable increase in gas-exchange surface area. The step designated secondary septation includes elastogenesis from interstitial fibroblasts.

Publication Title

Gene expression profiling in lung fibroblasts reveals new players in alveolarization.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE102067
An RNAi screen reveals an essential role for HIPK4 in human skin epithelial differentiation from iPSCs
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Molecular mechanisms that are responsible for the development of human skin epithelial cells are not completely understood so far. As a consequence, the efficiency to establish a pure skin epithelial cell population from human induced pluripotent stem cells (hiPSC) remains poor. Using an approach including RNA interference and high-throughput imaging of early epithelial cells, we could identify candidate kinases which are involved in skin epithelial differentiation. Among them, we found HIPK4 to be an important inhibitor of this process. Indeed, its silencing increased the amount of generated skin epithelial precursors, increased the amount of generated keratinocytes and improved growth and differentiation of organotypic cultures, allowing for the formation of a denser basal layer and stratification with the expression of several keratins. Our data bring substantial input in the regulation of human skin epithelial differentiation and for improving differentiation protocols from pluripotent stem cells.

Publication Title

An RNAi Screen Reveals an Essential Role for HIPK4 in Human Skin Epithelial Differentiation from iPSCs.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE61692
Expression data from OVCAR-3 cells overexpressing histone H1.3
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Ovarian cancer is a deadly gynecological malignancy for which novel biomarkers and therapeutic targets are imperative for improving survival. To investigate the role of histone H1 in ovarian cancer cells, we overexpress a histone H1 variant, H1.3, in the OVCAR-3 epithelial ovarian cancer cell line. RNA was extracted from OV-3/H1.3(H) cells (OVCAR-3 with overexpression of H1.3) and control cells of OVCAR-3 transfected with vectors without H1.3. The microarray chip used was human Affymetrix ST1.0 array. Gene expression changes caused by overexpression of H1.3 in OVCAR-3 cells were identified.

Publication Title

Histone h1.3 suppresses h19 noncoding RNA expression and cell growth of ovarian cancer cells.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP186927
AmpliSeq transcriptome profiling of human adipose tissue progenitor cell types
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Three different progenitor cell subsets in subcutaneous and visceral adipose tissues derived from 5 obese patients were subjected to AmpliSeq transcriptome profiling. Transcriptomic profiles were analyzed to compare progenitor cell subsets and the impact of subcutaneous and visceral adipose tissue location. Overall design: Transcriptomic profiling of 3 different progenitor cell types in subcutaneous and visceral adipose tissues derived from 5 obese patients (3X2X5=30 samples).

Publication Title

Lobular architecture of human adipose tissue defines the niche and fate of progenitor cells.

Sample Metadata Fields

Subject

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accession-icon GSE137110
Chronic mucocutaneous candidiasis and connective tissue disorder in humans with impaired JNK1-dependent responses to IL-17A/F and TGF-?
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Chronic mucocutaneous candidiasis and connective tissue disorder in humans with impaired JNK1-dependent responses to IL-17A/F and TGF-β.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment, Time

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accession-icon GSE16458
A simple method to integrate different versions of Affymetrix microarrays using duplicate samples
  • organism-icon Rattus norvegicus
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

The size and scope of microarray experiments continue to increase. However, datasets generated on different platforms or at different centres contain biases. Improved techniques are needed to remove platform- and batch-specific biases. One experimental control is the replicate hybridization of a subset of samples at each site or on each platform to learn the relationship between the two platforms. To date, no algorithm exists to specifically use this type of control. LTR is a linear-modelling-based algorithm that learns the relationship between different microarray batches from replicate hybridizations. LTR was tested on a new benchmark dataset of 20 samples hybridized to different Affymetrix microarray platforms. Before LTR, the two platforms were significantly different; application of LTR removed this bias. LTR was tested with six separate data pre-processing algorithms, and its effectiveness was independent of the pre-processing algorithm. Sample-size experiments indicate that just three replicate hybridizations can significantly reduce bias. An R library implementing LTR is available.

Publication Title

LTR: Linear Cross-Platform Integration of Microarray Data.

Sample Metadata Fields

Sex

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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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