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accession-icon GSE44292
Gene Expression data from mouse bone marrow derived macrophages treated with different inflammatory stimuli
  • organism-icon Mus musculus
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

The activation profiles of macrophages under different immune and inflammatory conditions have generated great interest. LPS, in particular, is a commonly used in vitro model of infection and inflammation studies in macrophages. We have used gene expression microarrays to define the effects of each of three variables; LPS dose, LPS vs. interferons beta and gamma, and genetic background on the transcriptional response of mouse bone marrow-derived macrophages

Publication Title

Analysis of the transcriptional networks underpinning the activation of murine macrophages by inflammatory mediators.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP049257
A negative feedback loop of transcription factors specifies alternative dendritic cell chromatin states (RNA-Seq)
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq1500

Description

During hematopoiesis, cells originating from the same stem cell reservoir differentiate into distinct cell types. The mechanisms enabling common progenitors to differentiate into distinct cell fates are not fully understood. Here, we identify chromatin-regulating and cell-fate-determining transcription factors (TF) governing dendritic cell (DC) development by annotating the enhancer and promoter landscapes of the DC lineage. Combining these analyses with detailed over-expression, knockdown and ChIP-Seq studies, we show that Irf8 functions as a plasmacytoid DC epigenetic and fate-determining TF, regulating massive, cell-specific chromatin changes in thousands of pDC enhancers. Importantly, Irf8 forms a negative feedback loop with Cebpb, a monocyte-derived DC epigenetic fate-determining TF. We show that using this circuit logic, differential activity of TF can stably define epigenetic and transcriptional states, regardless of the microenvironment. More broadly, our study proposes a general paradigm that allows closely related cells with a similar set of signal-dependent factors to generate differential and persistent enhancer landscapes. Overall design: Here analyzed 2 experiments, each one contains samples of moDC and pDC ex vivo cultured cells. The first experiment contains 32 samples of moDC and pDC following stimulation with various TLR stimulators. The second experiment contains 8 samples of moDC and pDC following perturbations; Cebpb and Irf8 knock down or over expression.

Publication Title

A negative feedback loop of transcription factors specifies alternative dendritic cell chromatin States.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP049253
Spinal cord injury (RNA sequencing data)
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq1500

Description

We investigated the gene expression profile of monocyte-derived macrophages and microglia following spinal cord injury. Moreover, we investigated the gene expression profole of M-CSF induced macrophages and new-born derived microglia following TGFb1 treatment. Overall design: monocyte-derived macrophages and microglia following spinal cord injury M-CSF induced macrophages and new-born derived microglia following TGFb1 treatment

Publication Title

Chronic exposure to TGFβ1 regulates myeloid cell inflammatory response in an IRF7-dependent manner.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP028868
RNA-Seq global gene expression in lung tissue at ten time points during a 7-day time course of infection
  • organism-icon Mus musculus
  • sample-icon 46 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Hundreds of immune cell types work in coordination to maintain tissue homeostasis. Upon infection, dramatic changes occur with the localization, migration and proliferation of the immune cells to first alert the body of the danger, confine it to limit spreading, and finally extinguish the threat and bring the tissue back to homeostasis. Since current technologies can follow the dynamics of only a limited number of cell types, we have yet to grasp the full complexity of global in vivo cell dynamics in normal developmental processes and disease. Here we devise a computational method, digital cell quantification (DCQ), which combines genomewide gene expression data with an immune cell compendium to infer in vivo dynamical changes in the quantities of 213 immune cell subpopulations. DCQ was applied to study global immune cell dynamics in mice lungs at ten time points during a 7-day time course of flu infection. We find dramatic changes in quantities of 70 immune cell types, including various innate, adaptive and progenitor immune cells. We focus on the previously unreported dynamics of four immune dendritic cell subtypes, and suggest a specific role for CD103+CD11b- cDCs in early stages of disease and CD8+ pDC in late stages of flu infection. Overall design: To study pathogenesis of Influenza infection, C57BL/6 mice (5 weeks) were infected intranasally with 4x103 PFU of influenza PR8 virus. We measured using RNA-Seq global gene expression in lung tissue at ten time points during a 7-day time course of infection, two infected individuals in each time point and four un-infected individuals as control. The lung organ was removed and transferred immediately into RNA Latter solution (Invitrogen).

Publication Title

Digital cell quantification identifies global immune cell dynamics during influenza infection.

Sample Metadata Fields

Age, Specimen part, Cell line, Subject, Time

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accession-icon SRP028867
RNA-Seq global gene expression of four Dendritic cells subpopulations from lung (CD8+ and CD8- pDCs, CD103-CD11b+ and CD103+CD11b- cDCs) of influenza infected mice at four time points following infection
  • organism-icon Mus musculus
  • sample-icon 28 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Hundreds of immune cell types work in coordination to maintain tissue homeostasis. Upon infection, dramatic changes occur with the localization, migration and proliferation of the immune cells to first alert the body of the danger, confine it to limit spreading, and finally extinguish the threat and bring the tissue back to homeostasis. Since current technologies can follow the dynamics of only a limited number of cell types, we have yet to grasp the full complexity of global in vivo cell dynamics in normal developmental processes and disease. Here we devise a computational method, digital cell quantification (DCQ), which combines genomewide gene expression data with an immune cell compendium to infer in vivo dynamical changes in the quantities of 213 immune cell subpopulations. DCQ was applied to study global immune cell dynamics in mice lungs at ten time points during a 7-day time course of flu infection. We find dramatic changes in quantities of 70 immune cell types, including various innate, adaptive and progenitor immune cells. We focus on the previously unreported dynamics of four immune dendritic cell subtypes, and suggest a specific role for CD103+CD11b- cDCs in early stages of disease and CD8+ pDC in late stages of flu infection. Overall design: To better understand the physiological role of these differential dynamic changes in the DCs, we measured the genome-wide RNA expression of all four DC subpopulations from lung of influenza infected mice at four time points following infections (two mice per time-point). For sorting dendritic cells from lungs, the lungs from infected and control uninfected C57BL/6J mice were immersed in cold PBS, cut into small pieces in 5 ml DMEM media containing 10% Bovine Fetal Serum, the cell suspensions were grinded using 1ml syringe cup on a 70 µm cell strainers (BD Falcon). The cells were washed with ice cold PBS. Remaining red blood cells were lysed using ammonium chloride solution (Sigma). Cells were harvested, immersed 1ml FACS buffer [PBS+2% FBS, 1mM EDTA], Fc receptors were blocked with anti-mouse CD16/CD32, washed with FACS buffer and divided into two tubes for sorting cDC and pDC cells.

Publication Title

Digital cell quantification identifies global immune cell dynamics during influenza infection.

Sample Metadata Fields

Age, Specimen part, Cell line, Subject, Time

View Samples
accession-icon SRP041767
Expression data from embryonic day 15.5 atrioventricular canal regions were isolated from Scx-/- and Scx+/+ mice.
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Purpose: Our lab has previously shown that Scleraxis (Scx) is require for proper valve development in vivo. In order to fully explore gene networks regulated by Scx during the vital stages of valve remodeling , high throughput RNA-squencing was performed. Results:There were a total of 18,810 genes were detected. A total of 864 genes were differentially expressed Scx null AVC regions: 645 being upregulated and 217 downregulated. Overall design: In this data set, we include expression data from atrioventricular canal (AVC) regions from Scx null and wild-type littermate controls at embryonic day 15.5. A total of 6 samples were analyzed; 3 valve regions from E15.5 Scx-/- mice, and 3 from E15.5 Scx+/+ wild-type littermate controls. Differential expression read counts are ranked based on p-value (<0.05).

Publication Title

RNA-seq analysis to identify novel roles of scleraxis during embryonic mouse heart valve remodeling.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE17612
Comparison of post-mortem tissue from brain BA10 region between schizophrenic and control patients.
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Analysis of gene expression in two large schizophrenia cohorts identifies multiple changes associated with nerve terminal function.

Publication Title

Analysis of gene expression in two large schizophrenia cohorts identifies multiple changes associated with nerve terminal function.

Sample Metadata Fields

Sex, Age

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accession-icon GSE21935
Comparison of post-mortem tissue from Brodman Brain BA22 region between schizophrenic and control patients
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Transcriptional analysis of the superior temporal cortex (BA22) in schizophrenia: Pathway insight into disease pathology and drug development

Publication Title

Transcription and pathway analysis of the superior temporal cortex and anterior prefrontal cortex in schizophrenia.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE16792
Temporal changes of gene expression in rat kidney and lung, and the effect of prior growth inhibition on these changes
  • organism-icon Rattus norvegicus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Temporal changes of gene expression from 1-wk- to 5-wk-old rat in kidney and lung, and the effect of prior growth inhibition on these genetic changes.

Publication Title

Coordinated postnatal down-regulation of multiple growth-promoting genes: evidence for a genetic program limiting organ growth.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE3077
Dillution series comparison of Affymetrix and Illumina Expression Platforms
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The growth in popularity of RNA expression microarrays has been accompanied by concerns about the reliability of the data especially when comparing between different platforms. Here we present an evaluation of the reproducibility of microarray results using two platforms, Affymetrix GeneChips and Illumina BeadArrays. The study design is based on a dilution series of two human tissues (blood and placenta), tested in duplicate on each platform. By a variety of measures the two platforms yielded data of similar quality and properties. The results of a comparison between the platforms indicate very high agreement, particularly for genes which are predicted to be differentially expressed between the two tissues. Agreement was strongly correlated with the level of expression of a gene. Concordance was also improved when probes on the two platforms could be identified as being likely to target the same set of transcripts of a given gene. These results shed light on the causes or failures of agreement across microarray platforms. The set of probes we found to be most highly reproducible can be used by others to help increase confidence in analyses of other data sets using these platforms.

Publication Title

Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms.

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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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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