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accession-icon GSE19556
Transcriptional program of terminal granulocytic differentation
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

To characterize the transcriptional program that governs terminal granulocytic differentation in vivo, we performed comprehensive microarray analysis of human bone marrow population highly enriched for promyelocytes, myelocytes / metamyelocytes and neotrophils.

Publication Title

Human neutrophils secrete bioactive paucimannosidic proteins from azurophilic granules into pathogen-infected sputum.

Sample Metadata Fields

Specimen part

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accession-icon GSE42538
Knockdown of mineralocorticoid receptor or glucocorticoid receptor on human endometrial stromal cells and decidualization
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To clarify mineralcorticoid receptor and glucocorticoid receptor-dependent gene networks in decidualizing human endometrial stromal cells.

Publication Title

Induction of 11β-HSD 1 and activation of distinct mineralocorticoid receptor- and glucocorticoid receptor-dependent gene networks in decidualizing human endometrial stromal cells.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

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accession-icon SRP059850
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of GMP)
  • organism-icon Mus musculus
  • sample-icon 123 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP059903
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq from CMP)
  • organism-icon Mus musculus
  • sample-icon 85 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP059844
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of bone marrow lineage-negative Sca1+ CD117+ cells)
  • organism-icon Mus musculus
  • sample-icon 88 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP059848
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-/- GMP)
  • organism-icon Mus musculus
  • sample-icon 71 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP059873
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Irf8 KO GMP)
  • organism-icon Mus musculus
  • sample-icon 63 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP071150
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-/- Irf8-/- GMP)
  • organism-icon Mus musculus
  • sample-icon 47 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP059847
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-GFP GMP)
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP059904
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Irf8-GFP GMP)
  • organism-icon Mus musculus
  • sample-icon 37 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples