Generation of 3D tubular bile duct within human iPSC-derived liver organoid by incorporating human iPSC-derived blood vessel [RNA-seq]
RNA-seq (gene expression) · human · 10 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
- 10 samples: 3 × BVLO # vs 2 × LO #Groups 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
- Generation of human iPSC-derived 3D bile duct within liver organoid by incorporating human iPSC-derived blood vesselNature communications · 2024
Read the full summary ↓
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 GSE198888_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 PRJNA817246 and SRA study SRP364675. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 5 samples.
How we read this: 2 replicated groups read from 10 sample titles; they account for 5 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.
- GSM5959054 HE (day8)
- GSM5959055 HE (day10)
- GSM5959056 IH (day12)
- GSM5959057 IH (day14)
- GSM5959058 MH (day21)
- GSM5959059 LO #1 LO #
- GSM5959060 LO #2 LO #
- GSM5959061 BVLO #1 BVLO #
- GSM5959062 BVLO #2 BVLO #
- GSM5959063 BVLO #3 BVLO #
- GSE334500 Psychotropic-drug and neurotransmitter perturbation RNA-seq of human iPSC-derived cardiac and retinal organoids (ToxiPred) 96 samples shares ipsc-derived, organoid, rna-seq
- GSE277967 Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols [time-course bulk RNA-seq] 768 samples shares organoid, rna-seq
- GSE255626 Next generation sequencing from primary glioblastoma patient tissues (Total RNA-seq) 109 samples shares generation, rna-seq
- GSE282668 TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degeneration 54 samples shares generation, organoid
- GSE299171 Hypoimmunogenic hPSC-derived cardiac organoids for immune evasion and heart repair [bulkRNA-seq] 48 samples shares organoid, rna-seq
- GSE337246 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [scRNA-Seq organoids] 35 samples shares organoid, rna-seq
- GSE298244 Bulk RNA-seq of iPSC-derived macrophages exposed to disease-relevant stimuli 30 samples shares ipsc-derived, rna-seq
- 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, organoid
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.