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accession-icon GSE20752
Comparative Epigenomic Analysis of Murine and Human Adipogenesis
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 26 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

Comparative epigenomic analysis of murine and human adipogenesis.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE20697
Expression profiling of human adipose stromal cell (hASC) adipogenesis
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Human abdominal adipose tissue was obtained with informed consent from a 33-year old Caucasian female (BMI = 32.96 Kg/m2) undergoing lipoaspiration. Adipose stromal cells (hASCs) were isolated and differentiated into adipocytes in vitro.

Publication Title

Comparative epigenomic analysis of murine and human adipogenesis.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE12207
Biofilms and type III secretion are not mutually exclusive in Pseudomonas aeruginosa
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Biofilm formation and type III secretion have been shown to be reciprocally regulated in P. aeruginosa, and it has been suggested that factors related to acute infection may be incompatible

Publication Title

Biofilms and type III secretion are not mutually exclusive in Pseudomonas aeruginosa.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE58193
Characterizing the profiles of Ebf1 in mouse fat cells.
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

gene expression data from mouse adipocyte, with and without Ebf1 knock-down

Publication Title

Early B-cell factor-1 (EBF1) is a key regulator of metabolic and inflammatory signaling pathways in mature adipocytes.

Sample Metadata Fields

Specimen part

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accession-icon GSE20696
Expression profiling of 3T3-L1 adipogenesis
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

3T3-L1 pre-adipocyte cells were grown to confluence and induced to differentiate in adipogeneic media.

Publication Title

Comparative epigenomic analysis of murine and human adipogenesis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP072289
Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Gene expression heterogeneity in the pluripotent state of mouse embryonic stem cells (mESCs) has been increasingly well-characterized. In contrast, exit from pluripotency and lineage commitment have not been studied systematically at the single-cell level. Here we measured the gene expression dynamics of retinoic acid driven mESC differentiation using an unbiased single-cell transcriptomics approach. We found that the exit from pluripotency marks the start of a lineage bifurcation as well as a transient phase of susceptibility to lineage specifying signals. Our study revealed several transcriptional signatures of this phase, including a sharp increase of gene expression variability and a handover between two classes of transcription factors. In summary, we provide a comprehensive analysis of lineage commitment at the single cell level, a potential stepping stone to improved lineage control through timing of differentiation cues. Overall design: Bulk and single-cell RNA-seq (SCRB-seq and SMART-seq) of mouse embryonic stem cells after different periods of continuous exposure to retinoic acid. Bulk RNA-seq of cell lines derived after retinoic exposure and after differentiation with retinoic acid and MEK inhibitor combined.

Publication Title

Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP066440
Simultaneous pathway activity inference and global gene expression analysis using RNA-sequencing [myd88]
  • organism-icon Mus musculus
  • sample-icon 383 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Two 96-well plates per genotype wild type and Myd88 knockout, 4 hour time series in 0.5 hr increments Overall design: Myd88 BMDM transcriptional profiling to complement TF-seq data

Publication Title

Simultaneous Pathway Activity Inference and Gene Expression Analysis Using RNA Sequencing.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Treatment, Subject, Time

View Samples
accession-icon SRP066443
Simultaneous pathway activity inference and global gene expression analysis using RNA-sequencing [halofuginone]
  • organism-icon Mus musculus
  • sample-icon 120 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Bone marrow derived macrophages treated with small molecules and stimulated with LPS Overall design: Wild-type BMDMs pretreated with small molecules for 30 minutes prior to stimulation with LPS

Publication Title

Simultaneous Pathway Activity Inference and Gene Expression Analysis Using RNA Sequencing.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Treatment, Subject, Time

View Samples
accession-icon SRP066437
Simultaneous pathway activity inference and global gene expression analysis using RNA-sequencing [SM screen]
  • organism-icon Mus musculus
  • sample-icon 96 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Bone marrow derived macrophages treated with small molecules and stimulated with LPS Overall design: Wild-type BMDMs pretreated with small molecules for 30 minutes prior to stimulation with LPS

Publication Title

Simultaneous Pathway Activity Inference and Gene Expression Analysis Using RNA Sequencing.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Treatment, Subject

View Samples
accession-icon SRP033135
Pseudo-temporal ordering of individual cells reveals regulators of differentiation
  • organism-icon Homo sapiens
  • sample-icon 384 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500, IlluminaHiSeq2000

Description

Single-cell expression profiling by RNA-Seq promises to exploit cell-to-cell variation in gene expression to reveal regulatory circuitry governing cell differentiation and other biological processes. Here, we describe Monocle, a novel unsupervised algorithm for ordering cells by progress through differentiation that dramatically increases temporal resolution of expression measurements. This reordering unmasks switch-like changes in expression of key regulatory factors, reveals sequentially organized waves of gene regulation, and exposes regulators of cell differentiation. A functional screen confirms that a number of these regulators dramatically alter the efficiency of myoblast differentiation, demonstrating that single-cell expression analysis with Monocle can uncover new regulators even in well-studied systems. Overall design: We selected primary human myoblasts as a model system of cell differentiation to investigate whether ordering cells by progress revealed new regulators of the process. We sequenced RNA-Seq libraries from each of several hundred cells taken over a time-course of serum-induced differentiation. Please note that this dataset is a single-cell RNA-Seq data set, and each cell comes from a capture plate. Thus, each well of the plate was scored and flagged with several QC criteria prior to library construction, which are provided as sample characteristics; CONTROL indicates that this library is a off-chip tube control library constructed from RNA of approximately 250 cells and ''DEBRIS'' indicates that the well contained visible debris (and may or may not include a cell). Libraries marked DEBRIS thus cannot be confirmed to come from a single cell.

Publication Title

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.

Sample Metadata Fields

No sample metadata fields

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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