Polygenic Risk for Alcohol Use Disorder Affects Cellular Responses to Ethanol Exposure in a Human Microglial Cell Model II
RNA-seq (gene expression) · human · 18 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
- 18 samples
- 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
- Polygenic risk for alcohol use disorder affects cellular responses to ethanol exposure in a human microglial cell modelScience advances · 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 GSE271585_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 PRJNA1132252 and SRA study SRP518183. Searching any of these in the dataset finder brings you back here.
The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Sample titles run ipsc204 … ipsc929 and carry no group information.
- GSM8380087 ipsc204
- GSM8380088 ipsc59
- GSM8380089 ipsc98
- GSM8380090 ipsc203
- GSM8380091 ipsc260
- GSM8380092 ipsc528
- GSM8380093 ipsc864
- GSM8380094 ipsc179
- GSM8380095 ipsc92
- GSM8380096 ipsc838
- GSM8380097 ipsc206
- GSM8380098 ipsc618
- GSM8380099 ipsc28
- GSM8380100 ipsc196
- GSM8380101 ipsc399
- GSM8380102 ipsc608
- GSM8380103 ipsc884
- GSM8380104 ipsc929
- GSE320486 Chronic PFOA and PFOS Exposure Triggers Cellular Oxidative Stress and Alters Lipid Levels as Revealed through Multi-omics Analysis 27 samples shares cellular, exposure
- GSE255685 Age-related transcriptomic differences in peripheral blood of adolescents with major depressive disorder 279 samples shares disorder
- GSE251778 Sex-specific and multiomic integration enhance accuracy of peripheral blood biomarkers of major depressive disorder [RNA-Seq] 169 samples shares disorder
- GSE334651 Alternative splicing- and gene fusion-derived neoepitopes in MASLD-associated hepatocellular carcinoma 120 samples shares cellular
- GSE272681 The cellular hierarchy of acute myeloid leukemia informs personalized treatment 108 samples shares cellular
- GSE208732 Mapping functional to morphological variation reveals the basis of regional extracellular matrix subversion and nerve invasion in pancreatic cancer [RNA-seq] 102 samples shares cellular
- GSE285963 Transcriptome profile of hepatocellular carcinoma in patients with atezolizumab plus bevacizumab therapy. 84 samples shares cellular
- GSE231854 The heterogeneity analysis of hepatocellular carcinoma and combined hepatocellular cholangiocarcinoma 81 samples shares cellular
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.