mRNA profiles of activated hematopoietic stem cells under several conditions [RNA-Seq]
RNA-seq (gene expression) · mouse · 20 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Mus musculus (mouse)
- Samples
- 20 samples: 20 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE279409_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1172664 and SRA study SRP538430. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 20 sample titles: 20 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8569460 [RNA-Seq] EPCRLow HSCs cultured under control conditions for 1 day (1)
- GSM8569461 [RNA-Seq] EPCRLow HSCs cultured under control conditions for 1 day (2)
- GSM8569462 [RNA-Seq] EPCRLow HSCs cultured under control conditions for 1 day (3)
- GSM8569463 [RNA-Seq] EPCRLow HSCs cultured under control conditions for 1 day (4)
- GSM8569464 [RNA-Seq] EPCRHigh HSCs cultured under control conditions for 1 day (1)
- GSM8569465 [RNA-Seq] EPCRHigh HSCs cultured under control conditions for 1 day (2)
- GSM8569466 [RNA-Seq] EPCRHigh HSCs cultured under control conditions for 1 day (3)
- GSM8569467 [RNA-Seq] EPCRHigh HSCs cultured under control conditions for 1 day (4)
- GSM8569468 [RNA-Seq] EPCRLow HSCs generated after 4-daya culture of EPCRHigh HSCs under control conditions for 1 day (1)
- GSM8569469 [RNA-Seq] EPCRLow HSCs generated after 4-daya culture of EPCRHigh HSCs under control conditions for 1 day (2)
- GSM8569470 [RNA-Seq] EPCRLow HSCs generated after 4-daya culture of EPCRHigh HSCs under control conditions for 1 day (3)
- GSM8569471 [RNA-Seq] EPCRLow HSCs generated after 4-daya culture of EPCRHigh HSCs under control conditions for 1 day (4)
- GSM8569472 [RNA-Seq] EPCRHigh HSCs generated after 4-daya culture of EPCRHigh HSCs under control conditions for 1 day (1)
- GSM8569473 [RNA-Seq] EPCRHigh HSCs generated after 4-daya culture of EPCRHigh HSCs under control conditions for 1 day (2)
- GSM8569474 [RNA-Seq] EPCRHigh HSCs generated after 4-daya culture of EPCRHigh HSCs under control conditions for 1 day (3)
- GSM8569475 [RNA-Seq] EPCRHigh HSCs generated after 4-daya culture of EPCRHigh HSCs under control conditions for 1 day (4)
- GSM8569476 [RNA-Seq] EPCRHigh HSCs expanded after 4-daya culture of EPCRHigh HSCs in the presence of R162 (1)
- GSM8569477 [RNA-Seq] EPCRHigh HSCs expanded after 4-daya culture of EPCRHigh HSCs in the presence of R162 (2)
- GSM8569478 [RNA-Seq] EPCRHigh HSCs expanded after 4-daya culture of EPCRHigh HSCs in the presence of R162 (3)
- GSM8569479 [RNA-Seq] EPCRHigh HSCs expanded after 4-daya culture of EPCRHigh HSCs in the presence of R162 (4)
- GSE265909 yHSC and oHSC scRNAseq with oHSC AThi ATlo Index Sorting. Assessing the transcriptional changes associated with autophagy engagement in old hematopoietic stem cells at single cell resolution. [scRNA-Seq] 563 samples shares hematopoietic, rna-seq, stem
- GSE266509 A Bcl11a-driven mechanism maintaining hematopoietic stem cell functionality gives rise to dysfunction during aging [RNA-Seq] 52 samples shares hematopoietic, rna-seq, stem
- GSE339586 Extensive Crosstalk between BMP and Notch Signaling Pathways in Activated Adult Muscle Stem Cells [RNA-seq III] 24 samples shares activated, rna-seq, stem
- GSE276137 The ac4C acetyltransferase Nat10 promotes RNA stability to support hematopoietic stem cell fate [RNA-seq-32D] 24 samples shares hematopoietic, rna-seq, stem
- GSE289635 Fabp4 is Essential for the Maintenance of Leukemia Stem Cells while Sparing Hematopoietic Stem Cells [bulkRNA-seq] 18 samples shares hematopoietic, rna-seq, stem
- GSE286398 Lysine-specific demethylase 1 regulates hematopoietic stem cell expansion and myeloid cell differentiation [scRNA-seq] 13 samples shares hematopoietic, rna-seq, stem
- GSE222941 Endomucin marks quiescent long-term multi-lineage repopulating hematopoietic stem cells and is essential for their transendothelial migration [RNA-seq: wildtype_EMCN] 11 samples shares hematopoietic, rna-seq, stem
- GSE277443 EMP1 preserves hematopoietic stem cell potential under homeostasis and radiation-induced injury by alleviating ER stress [ER-stress RNA-seq] 10 samples shares hematopoietic, rna-seq, stem
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.