RNA-Seq data of mouse retina, retinal pigment epithelium and cones
RNA-seq (gene expression) · mouse · 254 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
- 254 samples: 28 conditions, mostly in duplicateGroups 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
- Cone photoreceptor differentiation regulated by thyroid hormone transporter MCT8 in the retinal pigment epitheliumProceedings of the National Academy of Sciences of the United States of America · 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 GSE254669_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 PRJNA1071483 and SRA study SRP487055. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 248 samples.
How we read this: 28 replicated groups read from 254 sample titles; they account for 248 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.
- GSM8048170 2m_cone_ctrl_sup_01 2m_cone_ctrl_sup
- GSM8048171 2m_cone_ctrl_sup_02 2m_cone_ctrl_sup
- GSM8048172 2m_cone_ctrl_sup_03 2m_cone_ctrl_sup
- GSM8048173 2m_cone_ctrl_sup_04 2m_cone_ctrl_sup
- GSM8048174 2m_cone_ctrl_sup_05 2m_cone_ctrl_sup
- GSM8048175 2m_cone_ctrl_sup_06 2m_cone_ctrl_sup
- GSM8048176 2m_cone_ctrl_sup_07 2m_cone_ctrl_sup
- GSM8048177 2m_cone_ctrl_sup_08 2m_cone_ctrl_sup
- GSM8048178 2m_cone_ctrl_sup_09 2m_cone_ctrl_sup
- GSM8048179 2m_cone_ctrl_sup_10 2m_cone_ctrl_sup
- GSM8048180 2m_cone_ctrl_sup_11 2m_cone_ctrl_sup
- GSM8048181 2m_cone_ctrl_sup_12 2m_cone_ctrl_sup
- GSM8048182 2m_cone_ctrl_sup_13 2m_cone_ctrl_sup
- GSM8048183 2m_cone_ctrl_sup_14 2m_cone_ctrl_sup
- GSM8048184 2m_cone_ctrl_sup_15 2m_cone_ctrl_sup
- GSM8048185 2m_cone_ctrl_sup_16 2m_cone_ctrl_sup
- GSM8048186 2m_cone_ctrl_sup_17 2m_cone_ctrl_sup
- GSM8048187 2m_cone_ctrl_sup_18 2m_cone_ctrl_sup
- GSM8048188 2m_cone_ctrl_sup_19 2m_cone_ctrl_sup
- GSM8048189 2m_cone_ctrl_sup_20 2m_cone_ctrl_sup
- GSM8048190 2m_cone_ctrl_sup_21 2m_cone_ctrl_sup
- GSM8048191 2m_cone_ctrl_sup_22 2m_cone_ctrl_sup
- GSM8048192 2m_cone_ctrl_sup_23 2m_cone_ctrl_sup
- GSM8048193 2m_cone_ctrl_sup_24 2m_cone_ctrl_sup
- GSM8048194 2m_cone_ctrl_sup_25 2m_cone_ctrl_sup
- GSM8048195 2m_cone_ctrl_sup_26 2m_cone_ctrl_sup
- GSM8048196 2m_cone_ctrl_sup_27 2m_cone_ctrl_sup
- GSM8048197 2m_cone_ctrl_sup_28 2m_cone_ctrl_sup
- GSM8048198 2m_cone_ctrl_sup_29 2m_cone_ctrl_sup
- GSM8048199 2m_cone_ctrl_sup_30 2m_cone_ctrl_sup
- GSM8048200 2m_cone_ctrl_sup_31 2m_cone_ctrl_sup
- GSM8048201 2m_cone_ctrl_sup_32 2m_cone_ctrl_sup
- GSM8048202 2m_cone_ctrl_sup_33 2m_cone_ctrl_sup
- GSM8048203 2m_cone_ctrl_sup_34 2m_cone_ctrl_sup
- GSM8048204 2m_cone_ctrl_sup_35 2m_cone_ctrl_sup
- GSM8048205 2m_cone_ctrl_sup_36 2m_cone_ctrl_sup
- GSM8048206 2m_cone_ctrl_sup_37 2m_cone_ctrl_sup
- GSM8048207 2m_cone_ctrl_sup_38 2m_cone_ctrl_sup
- GSM8048208 2m_cone_ctrl_sup_39 2m_cone_ctrl_sup
- GSM8048209 2m_cone_ctrl_sup_40 2m_cone_ctrl_sup
+ 214 more — browse all 254 samples with per-sample file links →
- GSE173999 Single-cel RNA-seq of Mouse Olfactory Epithelium for Understanding Age-associated Neuronal Injury Response 19 samples shares epithelium, rna-seq
- GSE326100 scRNA-seq of mouse cochlea organoid cells 768 samples shares rna-seq
- GSE311449 Single cell RNA-seq of mouse brain vascular cells with Smart-seq2 method 391 samples shares rna-seq
- GSE319614 Bulk RNA-seq transcriptome profiling of hippocampus across 17 autism spectrum disorder mouse models 269 samples shares rna-seq
- GSE326452 Bulk RNA-seq of mouse brain following closed head injury: role of IL-1R1 signaling 200 samples shares rna-seq
- GSE264105 Plate-based scRNA-seq of plasma-positive microglia and plasma-negative microglia in young mice 1111 samples shares rna-seq
- GSE277789 Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq-add] 830 samples shares rna-seq
- GSE330728 Single-nucleus RNA-seq atlas of 17 ASD-risk mouse lines under early-postnatal fluoxetine or lithium exposure (4-plex On-Chip Multiplexed) 53 samples shares 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.