RNA-seq profiling of human hematopoietic cell populations across development.
RNA-seq (gene expression) · human · 106 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
- Homo sapiens (human)
- Samples
- 106 samples: 106 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.
- Paper
- MYCT1 controls environmental sensing in human haematopoietic stem cellsNature · 2024
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 GSE233478_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 PRJNA976325 and SRA study SRP439640. 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 106 sample titles: 106 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.
- GSM7429069 FL11-HSC_CMX-RNU-201
- GSM7429070 CB04-HSC_CMX-RNU-072
- GSM7429071 AGM06-endo_CMX-RNU-032
- GSM7429072 AGM06-HSPC_CMX-RNU-033
- GSM7429073 AGM06-HPC_CMX-RNU-034
- GSM7502138 FPL06-endo_CMX-RNU-035
- GSM7502139 FPL06-HSPC_CMX-RNU-036
- GSM7502140 FPL06-HPC_CMX-RNU-037
- GSM7502141 FL10-HSC_CMX-RNU-056a
- GSM7502142 FL10-CMP_CMX-RNU-059a
- GSM7502143 FL10-MEP_CMX-RNU-060a
- GSM7502144 AGM10-endo_CMX-RNU-060
- GSM7502145 FL10-GMP_CMX-RNU-061a
- GSM7502146 AGM10-HSPC_CMX-RNU-061
- GSM7502147 FL10-MoP_CMX-RNU-062a
- GSM7502148 AGM10-HPC_CMX-RNU-062
- GSM7502149 FL10-CDP_CMX-RNU-063a
- GSM7502150 FL10-CLP2_CMX-RNU-065a
- GSM7502151 ABM01-HSC_CMX-RNU-066a
- GSM7502154 AGM11-endo_CMX-RNU-066
- GSM7502157 AGM11-HSPC_CMX-RNU-067
- GSM7502161 ABM01-CMP_CMX-RNU-068a
- GSM7502163 AGM11-HPC_CMX-RNU-068
- GSM7502164 ABM01-MEP_CMX-RNU-069a
- GSM7502165 ABM01-GMP_CMX-RNU-070a
- GSM7502166 ABM01-MoP_CMX-RNU-071a
- GSM7502167 ABM01-CDP_CMX-RNU-072a
- GSM7502168 ABM01-LMPP_CMX-RNU-073a
- GSM7502169 ABM01-CLP1_CMX-RNU-074a
- GSM7502170 CB04-CMP_CMX-RNU-075
- GSM7502171 ABM02-HSC_CMX-RNU-076a
- GSM7502172 CB04-MEP_CMX-RNU-076
- GSM7502173 CB04-GMP_CMX-RNU-077
- GSM7502174 ABM02-CMP_CMX-RNU-078a
- GSM7502175 CB04-MoP_CMX-RNU-078
- GSM7502176 ABM02-MEP_CMX-RNU-079a
- GSM7502177 ABM02-GMP_CMX-RNU-080a
- GSM7502178 CB04-CLP1_CMX-RNU-080
- GSM7502179 ABM02-MoP_CMX-RNU-081a
- GSM7502180 CB04-CLP2_CMX-RNU-081
+ 66 more — browse all 106 samples with per-sample file links →
- GSE327707 Sorted bulk RNA-seq profiling of human peripheral blood mononuclear cell populations across diverse in vitro immune stimuli 150 samples shares populations, rna-seq, across
- GSE298173 Circulating immune cell signature analysis in HFpEF across species [RNA-Seq - human] 18 samples shares rna-seq, across
- GSE318490 Single-cell RNA-seq of tumor samples from six advanced HGSOC patients across treatment stages (pre-NACT, post-NACT and platinum-sensitive recurrence) 10 samples shares rna-seq, across
- GSE217313 The evolution of the type I IFN transcriptional response across human populations 46 samples shares populations, across
- GSE317207 Transcriptomic profiling of human hepatocellular carcinoma biopsy samples using bulk RNA-seq 33 samples shares rna-seq
- GSE310058 Single-nucleus transcriptomic profiling of human lung tissue in chronic obstructive pulmonary disease (COPD) [snRNA-seq] 149 samples shares rna-seq
- GSE342790 Development-inspired approach for the derivation of functional and transplantable salivary gland organoids from human pluripotent stem cells [RNA-Seq] 16 samples shares rna-seq
- GSE327167 Single-cell RNA-seq profiling of pleural mesothelioma and comparator pleural specimens 113 samples shares rna-seq
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.