3D Human iPSC-Derived Cardiac Organoids for Antifibrotic Drug Screening
RNA-seq (gene expression) · human · 12 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
- 12 samples: 4 × A vs 4 × B vs 4 × CGroups 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 GSE341748_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 PRJNA1503794 and SRA study SRP722291. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 3 replicated groups read from 12 sample titles; they account for 12 of them. 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.
- GSM9916086 A1 A
- GSM9916087 A2 A
- GSM9916088 A3 A
- GSM9916089 A4 A
- GSM9916090 B1 B
- GSM9916091 B2 B
- GSM9916092 B3 B
- GSM9916093 B4 B
- GSM9916094 C1 C
- GSM9916095 C2 C
- GSM9916096 C3 C
- GSM9916097 C4 C
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- GSE301365 Single-cell analysis of human iPSC-derived midbrain organoids generated with triphasic Wnt modulation combined with a dynamic bioreactor 30 samples shares ipsc-derived, organoids
- GSE275078 In vitro drug screening of RAF/MEK/ERK Inhibitors in combination with Autophagy inhibition in the context of two PDA Cell Lines 136 samples shares screening, drug
- GSE339602 Single-cell RNA sequencing of human iPSC-derived forebrain organoids following amyloid-β42 treatment, microglia co-culture, and maraviroc treatment 16 samples shares ipsc-derived, organoids
- GSE264741 Functional Screening and Transcriptomic Analysis Identify Novel Druggable Dependencies and Immunotherapy Targets in Desmoplastic Small Round Cell Tumor 124 samples shares screening, drug
- GSE280050 Senolytics rejuvenate aging cardiomyopathy in human cardiac organoids 15 samples shares organoids, cardiac
- GSE294532 Multi-layer stratified oncology platform utilizing transcriptomics, prostate cancer organoids, and modeling of drug response 63 samples shares organoids, drug
- GSE299171 Hypoimmunogenic hPSC-derived cardiac organoids for immune evasion and heart repair [bulkRNA-seq] 48 samples shares organoids, cardiac
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.