N6-methyladenosine modulate second cell fate decision by enhancing mRNA stability of pivotal transcription factors during primitive endoderm development [TBLC_RNAseq]
RNA-seq (gene expression) · mouse · 98 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
- 98 samples: 49 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.
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 GSE283382_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 PRJNA1193564 and SRA study SRP549056. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 98 samples.
How we read this: 49 replicated groups read from 98 sample titles; they account for 98 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.
- GSM8661186 TBLC_0h_rep1 TBLC_0h
- GSM8661187 TBLC_0h_rep2 TBLC_0h
- GSM8661188 TBLC_1h_rep1 TBLC_1h
- GSM8661189 TBLC_1h_rep2 TBLC_1h
- GSM8661190 TBLC_2h_rep1 TBLC_2h
- GSM8661191 TBLC_2h_rep2 TBLC_2h
- GSM8661192 TBLC_3h_rep1 TBLC_3h
- GSM8661193 TBLC_3h_rep2 TBLC_3h
- GSM8661194 diffTBLC_0h_rep1 diffTBLC_0h
- GSM8661195 diffTBLC_0h_rep2 diffTBLC_0h
- GSM8661196 diffTBLC_1h_rep1 diffTBLC_1h
- GSM8661197 diffTBLC_1h_rep2 diffTBLC_1h
- GSM8661198 diffTBLC_2h_rep1 diffTBLC_2h
- GSM8661199 diffTBLC_2h_rep2 diffTBLC_2h
- GSM8661200 diffTBLC_3h_rep1 diffTBLC_3h
- GSM8661201 diffTBLC_3h_rep2 diffTBLC_3h
- GSM8661202 diffTBLC_siNC1_0h_rep1 diffTBLC_siNC1_0h
- GSM8661203 diffTBLC_siNC1_0h_rep2 diffTBLC_siNC1_0h
- GSM8661204 diffTBLC_siNC1_1h_rep1 diffTBLC_siNC1_1h
- GSM8661205 diffTBLC_siNC1_1h_rep2 diffTBLC_siNC1_1h
- GSM8661206 diffTBLC_siNC1_2h_rep1 diffTBLC_siNC1_2h
- GSM8661207 diffTBLC_siNC1_2h_rep2 diffTBLC_siNC1_2h
- GSM8661208 diffTBLC_siNC1_3h_rep1 diffTBLC_siNC1_3h
- GSM8661209 diffTBLC_siNC1_3h_rep2 diffTBLC_siNC1_3h
- GSM8661210 diffTBLC_siVirma_0h_rep1 diffTBLC_siVirma_0h
- GSM8661211 diffTBLC_siVirma_0h_rep2 diffTBLC_siVirma_0h
- GSM8661212 diffTBLC_siVirma_1h_rep1 diffTBLC_siVirma_1h
- GSM8661213 diffTBLC_siVirma_1h_rep2 diffTBLC_siVirma_1h
- GSM8661214 diffTBLC_siVirma_2h_rep1 diffTBLC_siVirma_2h
- GSM8661215 diffTBLC_siVirma_2h_rep2 diffTBLC_siVirma_2h
- GSM8661216 diffTBLC_siVirma_3h_rep1 diffTBLC_siVirma_3h
- GSM8661217 diffTBLC_siVirma_3h_rep2 diffTBLC_siVirma_3h
- GSM8661218 diffTBLC_siNC2_0h_rep1 diffTBLC_siNC2_0h
- GSM8661219 diffTBLC_siNC2_0h_rep2 diffTBLC_siNC2_0h
- GSM8661220 diffTBLC_siNC2_1h_rep1 diffTBLC_siNC2_1h
- GSM8661221 diffTBLC_siNC2_1h_rep2 diffTBLC_siNC2_1h
- GSM8661222 diffTBLC_siNC2_2h_rep1 diffTBLC_siNC2_2h
- GSM8661223 diffTBLC_siNC2_2h_rep2 diffTBLC_siNC2_2h
- GSM8661224 diffTBLC_siNC2_3h_rep1 diffTBLC_siNC2_3h
- GSM8661225 diffTBLC_siNC2_3h_rep2 diffTBLC_siNC2_3h
+ 58 more — browse all 98 samples with per-sample file links →
- GSE294772 Single-Cell Epigenomics Uncovers Heterochromatin Instability and Transcription Factor Dysfunction during Mouse Brain Aging [snATAC-Seq] [10X Multiome] 142 samples shares transcription, stability
- GSE286046 Asymmetric Histone Inheritance Regulates Differential Transcription Re-initiation and Cell Fate Decisions in Mouse Olfactory Horizontal Basal Cells 96 samples shares transcription, decision
- GSE322779 Transcription factor TFEB antagonizes cardiac hypertrophy and failure by enhancing lysosomal capacity and mitochondrial function 16 samples shares transcription, enhancing
- GSE336756 Compartmentalisation of m6A (N6-methyladenosine) methylated RNA in somatic or axonal subcellular locations is dependent on Nerve Growth Factor (NGF) state in sympathetic neurons [Axon-meRIP-seq] 32 samples shares n6-methyladenosine
- GSE306448 Milk osteopontin protects against infant bronchiolitis by enhancing microbiome-mediated extramedullary DC hematopoiesis 32 samples shares enhancing
- GSE253581 Transcriptional profiling of CD11b+ microglia isolated from cerebellum and olfactory bulb-removed brains of K18-seeded P301L, PBS-injected P301L and PBS-injected FVB at 1-week, 1-month, and 3-months post-injection. 27 samples shares transcription
- GSE284504 Transcriptional profiling of brain from a zQ175 KI mouse model of Huntington's disease 335 samples shares transcription
- GSE237534 INO80 / SWR remodelers regulate Pol II transcription through BRD2 and chromatin landscape 217 samples shares transcription
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.