Gene expression profiles of human dermal fibroblasts and human pluripotent stem cells analyzed by bulk RNA-seq
RNA-seq (gene expression) · human · 69 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
- 69 samples: 69 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
- H1FOO-DD promotes efficiency and uniformity in reprogramming to naive pluripotencyStem cell reports · 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 GSE224698_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 PRJNA932227 and SRA study SRP421320. 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 69 sample titles: 69 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.
- GSM7029720 Primed OSKL iPSC_1 (bulkRNA-seq)
- GSM7029721 Primed OSKL iPSC_2 (bulkRNA-seq)
- GSM7029722 Primed OSKL iPSC_3 (bulkRNA-seq)
- GSM7029723 Primed OSKL iPSC_4 (bulkRNA-seq)
- GSM7029724 Primed OSKL iPSC_5 (bulkRNA-seq)
- GSM7029725 Primed OSKL iPSC_6 (bulkRNA-seq)
- GSM7029726 Primed OSKL iPSC_7 (bulkRNA-seq)
- GSM7029727 Primed OSKL iPSC_8 (bulkRNA-seq)
- GSM7029728 Primed OSKLH iPSC_1 (bulkRNA-seq)
- GSM7029729 Primed OSKLH iPSC_2 (bulkRNA-seq)
- GSM7029730 Primed OSKLH iPSC_3 (bulkRNA-seq)
- GSM7029731 Primed OSKLH iPSC_4 (bulkRNA-seq)
- GSM7029732 Primed OSKLH iPSC_5 (bulkRNA-seq)
- GSM7029733 Primed OSKLH iPSC_6 (bulkRNA-seq)
- GSM7029734 Primed OSKLH iPSC_7 (bulkRNA-seq)
- GSM7029735 Primed OSKLH iPSC_8 (bulkRNA-seq)
- GSM7029736 Primed H9 ESC (bulkRNA-seq)
- GSM7029737 KhES1 (bulkRNA-seq)
- GSM7029738 201B7 (bulkRNA-seq)
- GSM7029739 Naive H9 ESC (bulkRNA-seq)
- GSM7029740 Naive OSKL iPSC_1 (bulkRNA-seq)
- GSM7029741 Naive OSKL iPSC_2 (bulkRNA-seq)
- GSM7029742 Naive OSKL iPSC_3 (bulkRNA-seq)
- GSM7029743 Naive OSKL iPSC_4 (bulkRNA-seq)
- GSM7029744 Naive OSKL iPSC_5 (bulkRNA-seq)
- GSM7029745 Naive OSKL iPSC_6 (bulkRNA-seq)
- GSM7029746 Naive OSKLH iPSC_1 (bulkRNA-seq)
- GSM7029747 Naive OSKLH iPSC_2 (bulkRNA-seq)
- GSM7029748 Naive OSKLH iPSC_3 (bulkRNA-seq)
- GSM7029749 Naive OSKLH iPSC_4 (bulkRNA-seq)
- GSM7029750 Naive OSKLH iPSC_5 (bulkRNA-seq)
- GSM7029751 Naive OSKLH iPSC_6 (bulkRNA-seq)
- GSM7029752 Primed MOI15 iPSC_1 (bulkRNA-seq)
- GSM7029753 Primed MOI15 iPSC_2 (bulkRNA-seq)
- GSM7029754 Primed MOI15 iPSC_3 (bulkRNA-seq)
- GSM7029755 Primed MOI15 iPSC_4 (bulkRNA-seq)
- GSM7029756 Primed MOI15 iPSC_5 (bulkRNA-seq)
- GSM7029757 Primed MOI15 iPSC_6 (bulkRNA-seq)
- GSM7029758 Primed MOI15 iPSC_7 (bulkRNA-seq)
- GSM7029759 Primed MOI15 iPSC_8 (bulkRNA-seq)
+ 29 more — browse all 69 samples with per-sample file links →
- GSE330762 Kabuki syndrome type I fibroblast multi-omics dataset: bulk RNA-seq profiles from primary skin fibroblasts 19 samples shares fibroblasts, profiles, rna-seq, bulk
- GSE274217 METTL3-dependent m6A RNA methylation represses transposable elements derived enhancers to suppress naïve pluripotency in human pluripotent stem cells [RNA-Seq] 28 samples shares pluripotent, rna-seq, stem
- GSE342790 Development-inspired approach for the derivation of functional and transplantable salivary gland organoids from human pluripotent stem cells [RNA-Seq] 16 samples shares pluripotent, rna-seq, stem
- GSE287227 Transient SP140 inhibition unlocks hematopoietic stem cell fate from human pluripotent stem cells [scRNA-seq] 9 samples shares pluripotent, rna-seq, stem
- GSE262419 Informing Hazard Identification and Risk Characterization of Environmental Chemicals by Combining Transcriptomic and Functional Data from Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes 4558 samples shares pluripotent, stem
- GSE226482 Single cell RNA sequencing of spinal motor neurons and interneurons differentiated from isogenic FUS and TARDBP human induced pluripotent stem cell lines harbouring ALS-causative mutations 1415 samples shares pluripotent, stem
- GSE275647 Role of Cancer-Associated Fibroblasts in Prognostic Stratification of Advanced-Stage Gastric Cancer through Interacting with Endothelial and Malignant Epithelial Cells [AGC RNA-seq] 216 samples shares fibroblasts, rna-seq
- GSE293777 A high-risk osteoarthritis mutation in COL6A3 alters the mechanobiologic response of chondrocytes derived from human induced pluripotent stem cells 84 samples shares pluripotent, 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.