AV8 gene therapy and environmental exposure precipitate cholestatic liver disease in a mouse model of X-linked myotubular myopathy
RNA-seq (gene expression) · mouse · 26 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
- Mus musculus (mouse)
- Samples
- 26 samples: 26 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.
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 GSE264209_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 PRJNA1101466 and SRA study SRP502360. 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 26 sample titles: 26 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.
- GSM8214050 Mouse liver RNAseq data_WT and KO Chow 21 days - 1 KO
- GSM8214051 Mouse liver RNAseq data_KO RD 35days only - 1 KO Chow
- GSM8214052 Mouse liver RNAseq data_WT and KO Chow 35days only - 1 KO RD
- GSM8214053 Mouse liver RNAseq data_WT RD 35days only - 1_WT_CHOW
- GSM8214054 Mouse liver RNAseq data_WT RD 35days only - 1_WT_RD
- GSM8214055 Mouse liver RNAseq data_WT and KO Chow 21 days - 1 WT
- GSM8214056 Mouse liver RNAseq data_WT and KO Chow 21 days - 2 KO
- GSM8214057 Mouse liver RNAseq data_KO RD 35days only - 2_KO_CHOW
- GSM8214058 Mouse liver RNAseq data_KO RD 35days only - 2_KO_RD
- GSM8214059 Mouse liver RNAseq data_WT and KO Chow 21 days - 1
- GSM8214060 Mouse liver RNAseq data_WT and KO Chow 35days only - 2 KO RD
- GSM8214061 Mouse liver RNAseq data_WT and KO Chow 35days only - 2_WT_CHOW
- GSM8214062 Mouse liver RNAseq data_KO RD 35days only - 3_KO_CHOW
- GSM8214063 Mouse liver RNAseq data_ remaining 21 - 3_KO_RD
- GSM8214064 Mouse liver RNAseq data_WT and KO Chow 21 days - 3 WT
- GSM8214065 Mouse liver RNAseq data_WT RD 35days only - 3_WT_CHOW
- GSM8214066 Mouse liver RNAseq data_WT RD 35days only - 3_WT_CHOW - 3_WT_RD
- GSM8214067 Mouse liver RNAseq data_WT and KO Chow 21 days - 3 KO
- GSM8214068 Mouse liver RNAseq data_WT and KO Chow 21 days - 4 KO
- GSM8214069 Mouse liver RNAseq data_WT and KO Chow 35days only - 4_KO_CHOW
- GSM8214070 Mouse liver RNAseq data_KO RD 35days only - 4_KO_RD
- GSM8214071 Mouse liver RNAseq data_WT and KO Chow 21 days - 4 WT
- GSM8214072 Mouse liver RNAseq data_WT and KO Chow 35days only - 4_WT_CHOW
- GSM8214073 Mouse liver RNAseq data_WT RD 35days only - 4_WT_RD
- GSM8214074 Mouse liver RNAseq data_KO RD 35days only - 5_KO_RD
- GSM8214075 Mouse liver RNAseq data_KO RD 35days only - 8573_KOS_RD
- GSE327967 Transcriptional regulation of the main olfactory epithelium by environmental olfactory exposures 34 samples shares environmental, exposure
- GSE325788 Pregnancy precipitates metabolic imbalance and accelerates death in an animal model of mitochondrial cardiomyopathy 30 samples shares precipitate, myopathy
- GSE277525 Environmental dose of Bisphenol S exposure to brown adipose tissue accelerates aging 15 samples shares environmental, exposure
- GSE267022 Aconitate decarboxylase 1 mediates acute airway inflammatory response to environmental exposures 6 samples shares environmental, exposure
- GSE306911 Chronic exposure of PFOS at environmental-relevant concentration promotes TNBC aggressive phenotypes 6 samples shares environmental, exposure
- GSE289162 Plasticity of epigenomic aging creates vulnerabilities to early-life environmental exposures, reshaping adult cell- and direction-specific trajectories 54 samples shares environmental, exposure
- GSE206761 Transcriptome profile of thioacetamide treated mice injected with AAV8 TBG eGFP and AAV8 TBG miR34b/c 19 samples shares av8
- GSE249017 AMPK is necessary for Treg functional adaptation to microenvironmental stress during malignancy and viral pneumonia 41 samples shares environmental
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.