Simultaneous orthogonal cell engineering by a single CRISPR-Cas9 polyfunctional editor [RNA-seq T-cells B2M/TET2/TGFBR2]
RNA-seq (gene expression) · human · 14 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
- 14 samples: 6 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 GSE319117_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 PRJNA1422126 and SRA study SRP676276. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 6 replicated groups read from 14 sample titles; they account for 12 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.
- GSM9511029 Tripartite ETR targeting with an unrelated gRNA treated T cells, replicate 1.
- GSM9511030 Tripartite ETR targeting with an unrelated gRNA treated T cells, replicate 2.
- GSM9511031 Tripartite ETR targeting B2M with a full-length gRNA treated T cells, replicate 1 Tripartite ETR targetin…
- GSM9511032 Tripartite ETR targeting B2M with a full-length gRNA treated T cells, replicate 2 Tripartite ETR targetin…
- GSM9511033 Tripartite ETR targeting B2M with a truncated gRNA treated T cells, replicate1 Tripartite ETR targetin…
- GSM9511034 Tripartite ETR targeting B2M with a truncated gRNA treated T cells, replicate2 Tripartite ETR targetin…
- GSM9511035 Tripartite ETR targeting TET2 with a full-length gRNA treated T cells, replicate 1 Tripartite ETR targetin…
- GSM9511036 Tripartite ETR targeting TET2 with a full-length gRNA treated T cells, replicate 2 Tripartite ETR targetin…
- GSM9511037 Tripartite ETR targeting TET2 with a truncated gRNA treated T cells, replicate1 Tripartite ETR targetin…
- GSM9511038 Tripartite ETR targeting TET2 with a truncated gRNA treated T cells, replicate2 Tripartite ETR targetin…
- GSM9511039 Tripartite ETR targeting TGFBR2 with a full-length gRNA treated T cells, replicate 1 Tripartite ETR targetin…
- GSM9511040 Tripartite ETR targeting TGFBR2 with a full-length gRNA treated T cells, replicate 2 Tripartite ETR targetin…
- GSM9511041 Tripartite ETR targeting TGFBR2 with a truncated gRNA treated T cells, replicate1 Tripartite ETR targetin…
- GSM9511042 Tripartite ETR targeting TGFBR2 with a truncated gRNA treated T cells, replicate2 Tripartite ETR targetin…
- GSE293141 Simultaneous orthogonal cell engineering by a single CRISPR-Cas9 polyfunctional editor [RNA-seq K562] 9 samples shares polyfunctional, simultaneous, engineering, crispr-cas9, orthogonal
- GSE319115 Simultaneous orthogonal cell engineering by a single CRISPR-Cas9 polyfunctional editor [RNA-seq T-cells CD3D] 6 samples shares polyfunctional, simultaneous, engineering, crispr-cas9, orthogonal
- GSE293143 Simultaneous orthogonal cell engineering by a single CRISPR-Cas9 polyfunctional editor 84 samples shares polyfunctional, simultaneous, engineering, crispr-cas9, orthogonal
- 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
- GSE305029 TET2 drives myeloid cell fate acquisition through AGO2 modulation [RNA-seq, AGO2 KD transdifferentiation] 27 samples shares tet2
- GSE287524 RNASeq of TET2-mutant human HSPCs and monocytes 24 samples shares tet2
- GSE256159 Glucocorticoid promotes metastasis of colorectal cancer via co-regulation of glucocorticoid receptor and TET2 (RNA-Seq) 21 samples shares tet2
- 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
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.