RNA-seq of Monocyte-derived Macrophages and Hepatic Stellate Cell Activation after 72hr
RNA-seq (gene expression) · human · 28 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
- 28 samples: 28 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
- Diverse potential of secretome from natural killer cells and monocyte-derived macrophages in activating stellate cellsFrontiers in immunology · 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 GSE228088_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 PRJNA948019 and SRA study SRP428968. 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 28 sample titles: 28 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.
- GSM7113691 1_Hepatic_Stellate_Cell_Control_72h
- GSM7113692 2_Hepatic_Stellate_Cell_Control_72h
- GSM7113693 3_Hepatic_Stellate_Cell_Control_72h
- GSM7113694 1_Hepatic_Stellate_Cell_IL13_10ng_per_ml_72h
- GSM7113695 2_Hepatic_Stellate_Cell_IL13_10ng_per_ml_72h
- GSM7113696 3_Hepatic_Stellate_Cell_IL13_10ng_per_ml_72h
- GSM7113697 1_Hepatic_Stellate_Cell_TGFB1_5ng_per_ml_72h
- GSM7113698 2_Hepatic_Stellate_Cell_TGFB1_5ng_per_ml_72h
- GSM7113699 3_Hepatic_Stellate_Cell_TGFB1_5ng_per_ml_72h
- GSM7113700 1_Hepatic_Stellate_Cell_TNFA_20ng_per_ml_72h
- GSM7113701 2_Hepatic_Stellate_Cell_TNFA_20ng_per_ml_72h
- GSM7113702 3_Hepatic_Stellate_Cell_TNFA_20ng_per_ml_72h
- GSM7113703 1_M_CSF_IL_4_ IL_13
- GSM7113704 2_M_CSF_IL_4_ IL_13
- GSM7113705 3_M_CSF_IL_4_ IL_13
- GSM7113706 4_M_CSF_IL_4_ IL_13
- GSM7113707 5_M_CSF_IL_4_ IL_13
- GSM7113708 2_M_CSF_LPS_IFN_gamma
- GSM7113709 3_M_CSF_LPS_IFN_gamma
- GSM7113710 4_M_CSF_LPS_IFN_gamma
- GSM7113711 5_M_CSF_LPS_IFN_gamma
- GSM7113712 1_M_CSF_unstim
- GSM7113713 2_M_CSF_unstim
- GSM7113714 3_M_CSF_unstim
- GSM7113715 4_M_CSF_unstim
- GSM7113716 5_M_CSF_unstim
- GSM7113717 3_Monozyten_unstim
- GSM7113718 5_Monozyten_unstim
- GSE300680 A streamlined and comprehensive protocol for the generation and multi-omic analysis of human monocyte-derived macrophages [bulk RNA-Seq] 20 samples shares monocyte-derived, macrophages, rna-seq
- GSE341139 A conserved HAND2-BMP5-SMAD1/5/9 axis drives hepatic stellate cell activation and extracellular matrix overproduction in multiple fibrotic etiologies 10 samples shares activation, stellate, hepatic
- GSE276915 Hepatic stellate cell single cell atlas reveals a highly similar activation process across liver disease aetiologies 10 samples shares activation, stellate, hepatic
- GSE341616 A conserved HAND2-HAND2_OE-SMAD1/5/9 axis drives hepatic stellate cell activation and extracellular matrix overproduction in multiple fibrotic etiologies 5 samples shares activation, stellate, hepatic
- GSE281471 Targeting CD206+ macrophages disrupts the establishment of a key anti-tumor immune axis [Bulk RNA-seq] 243 samples shares macrophages, rna-seq
- GSE269009 RNA-seq of monocyte derived macrophages and dendritic cells in a Peruvian Tuberculosis cohort 227 samples shares macrophages, rna-seq
- GSE303856 CPSF73 activation and 3’ Pol II pausing are lost during read-through transcription after heat shock [RNA-seq] 14 samples shares activation, rna-seq
- GSE327289 Cerebrovascular Single-Nucleus RNA-Seq Reveals Heat Shock Activation and Vascular Remodeling in Alzheimer’s Disease and Primary Tauopathies 76 samples shares activation, 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.