Targeting T cell plasticity by pooled single cell CRISPR-screening in preclinical models of kidney and gut inflammation
Single-cell RNA-seq · mouse · 56 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 56 samples: 52 distinct titles, 1 of them repeatedGroups 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
- Targeting T cell plasticity in kidney and gut inflammation by pooled single-cell CRISPR screeningScience immunology · 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 GSE267740_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1112754 and SRA study SRP508314. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 56 sample titles: 52 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.
- GSM8274943 CropSeq NTN, Sample 1
- GSM8274944 CropSeq NTN, Sample 2
- GSM8274945 CropSeq NTN, Sample 3
- GSM8274946 CropSeq NTN, Sample 4
- GSM8274947 CropSeq NTN, Sample 5
- GSM8980163 Patient sample 1, GEX
- GSM8980164 Patient sample 1, TCR
- GSM8980165 Patient sample 1, ADT
- GSM8980166 Patient sample 2, GEX
- GSM8980167 Patient sample 2, TCR
- GSM8980168 Patient sample 2, ADT
- GSM8980169 Patient sample 3, GEX
- GSM8980170 Patient sample 3, TCR
- GSM8980171 Patient sample 3, ADT
- GSM8980172 Patient sample 4, GEX
- GSM8980173 Patient sample 4, TCR
- GSM8980174 Patient sample 4, ADT
- GSM8980175 Patient sample 5, GEX
- GSM8980176 Patient sample 5, TCR
- GSM8980177 Patient sample 5, ADT
- GSM8980178 Patient sample 6, GEX
- GSM8980179 Patient sample 6, TCR
- GSM8980180 Patient sample 6, ADT
- GSM8980181 Patient sample 7, GEX
- GSM8980182 Patient sample 7, TCR
- GSM8980183 Patient sample 7, ADT
- GSM8980184 Patient sample 8, GEX
- GSM8980185 Patient sample 8, TCR
- GSM8980186 Patient sample 8, ADT
- GSM8980187 Patient sample 9, GEX
- GSM8980188 Patient sample 9, TCR
- GSM8980189 Patient sample 10,GEX
- GSM8980190 Patient sample 10, TCR
- GSM8980191 Patient sample 10, ADT
- GSM8980192 Patient sample 11, GEX
- GSM8980193 Patient sample 11, TCR
- GSM8980194 Patient sample 11, ADT
- GSM8980195 CropSeq NTN 2, Sample 1, GEX
- GSM8980196 CropSeq NTN 2, Sample 1, ADT
- GSM8980197 CropSeq NTN 2, Sample 2, GEX
+ 16 more — browse all 56 samples with per-sample file links →
- GSE314854 Targeting Modulated Vascular Smooth Muscle Cells in Atherosclerosis via FAP-Directed Immunotherapy 102 samples shares targeting
- GSE297064 Targeting circulating mechanoresponsive monocytes and macrophages to reduce fibrosis 12 samples shares targeting
- GSE281472 Targeting CD206+ macrophages disrupts the establishment of a key anti-tumor immune axis 245 samples shares targeting
- GSE224832 Active repression of cell fate plasticity by PROX1 safeguards hepatocyte identity and prevents liver tumorigenesis. 104 samples shares plasticity
- GSE63782 Transcriptional plasticity promotes primary and acquired resistance to BET bromodomain inhibition 103 samples shares plasticity
- GSE249981 Non-canonical PRC1.1 licenses transcriptional response to enable Treg plasticity in immune adaptation. 70 samples shares plasticity
- GSE255372 Targeting CDK7 function in the RNA Polymerase II transcription cycle in inflammatory arthritis [ChIP-seq] 69 samples shares targeting
- GSE277861 Enalapril mitigates senescence and aging-related phenotypes by targeting antioxidative genes via phosphorylated Smad1/5/9 [RNA-seq] 68 samples shares targeting
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.