TET2 drives myeloid cell fate acquisition through AGO2 modulation [RNA-seq, AGO2 KD transdifferentiation]
RNA-seq (gene expression) · human · 27 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
- 27 samples: 9 conditions, mostly in triplicateGroups 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.
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 GSE305029_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 PRJNA1303737 and SRA study SRP607771. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 27 samples.
How we read this: 9 replicated groups read from 27 sample titles; they account for 27 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.
- GSM9161229 AGO2 KD, Region 1, 0 h, r1 AGO2 KD, Region 1, 0 h,
- GSM9161230 AGO2 KD, Region 1, 0 h, r2 AGO2 KD, Region 1, 0 h,
- GSM9161231 AGO2 KD, Region 1, 0 h, r3 AGO2 KD, Region 1, 0 h,
- GSM9161232 AGO2 KD, Region 1, 72 h, r1 AGO2 KD, Region 1, 72 h,
- GSM9161233 AGO2 KD, Region 1, 72 h, r2 AGO2 KD, Region 1, 72 h,
- GSM9161234 AGO2 KD, Region 1, 72 h, r3 AGO2 KD, Region 1, 72 h,
- GSM9161235 AGO2 KD, Region 1, 144 h, r1 AGO2 KD, Region 1, 144 …
- GSM9161236 AGO2 KD, Region 1, 144 h, r2 AGO2 KD, Region 1, 144 …
- GSM9161237 AGO2 KD, Region 1, 144 h, r3 AGO2 KD, Region 1, 144 …
- GSM9161238 AGO2 KD, Region 2, 0 h, r1 AGO2 KD, Region 2, 0 h,
- GSM9161239 AGO2 KD, Region 2, 0 h, r2 AGO2 KD, Region 2, 0 h,
- GSM9161240 AGO2 KD, Region 2, 0 h, r3 AGO2 KD, Region 2, 0 h,
- GSM9161241 AGO2 KD, Region 2, 72 h, r1 AGO2 KD, Region 2, 72 h,
- GSM9161242 AGO2 KD, Region 2, 72 h, r2 AGO2 KD, Region 2, 72 h,
- GSM9161243 AGO2 KD, Region 2, 72 h, r3 AGO2 KD, Region 2, 72 h,
- GSM9161244 AGO2 KD, Region 2, 144 h, r1 AGO2 KD, Region 2, 144 …
- GSM9161245 AGO2 KD, Region 2, 144 h, r2 AGO2 KD, Region 2, 144 …
- GSM9161246 AGO2 KD, Region 2, 144 h, r3 AGO2 KD, Region 2, 144 …
- GSM9161247 Control, 0 h, r1 Control, 0 h,
- GSM9161248 Control, 0 h, r2 Control, 0 h,
- GSM9161249 Control, 0 h, r3 Control, 0 h,
- GSM9161250 Control, 72 h, r1 Control, 72 h,
- GSM9161251 Control, 72 h, r2 Control, 72 h,
- GSM9161252 Control, 72 h, r3 Control, 72 h,
- GSM9161253 Control, 144 h, r1 Control, 144 h,
- GSM9161254 Control, 144 h, r2 Control, 144 h,
- GSM9161255 Control, 144 h, r3 Control, 144 h,
- GSE307201 TET2 drives myeloid cell fate acquisition through AGO2 modulation [RNA-seq, TET2 KD transdifferentiation] 12 samples shares tet2, ago2, transdifferentiation, acquisition, modulation, myeloid, rna-seq, drives
- GSE307340 TET2 drives myeloid cell fate acquisition through AGO2 modulation 61 samples shares tet2, ago2, acquisition, modulation, myeloid, drives
- GSE304943 TET2 drives myeloid cell fate acquisition through AGO2 modulation [ChIP-seq, TET2] 4 samples shares tet2, ago2, acquisition, modulation, myeloid, drives
- GSE298864 Retinoic acid and ascorbate synergize to suppress myeloid leukemia via TET2 activation [MV4-11 RNA-Seq] 12 samples shares tet2, myeloid, rna-seq
- GSE241584 Retinoic acid and ascorbate synergize to suppress myeloid leukemia via TET2 activation [U-937 RNA-Seq] 8 samples shares tet2, myeloid, rna-seq
- GSE210433 TET2 Mutant Clonal Hematopoiesis Enhances Severity of COVID-19 Related Cytokine Release Syndrome and is Associated with Increased Mortality [scRNA-seq] 34 samples shares tet2, rna-seq
- GSE256159 Glucocorticoid promotes metastasis of colorectal cancer via co-regulation of glucocorticoid receptor and TET2 (RNA-Seq) 21 samples shares tet2, rna-seq
- GSE261322 NF-κB- and TET2-mediated macrophage reprogramming overrides the anti-inflammatory effects of hypoxia and improves responses in human cancer (RNA-Seq I). 20 samples shares tet2, 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.