Transcriptomic Reprogramming of T Cells Underlies Rituximab Efficacy in Idiopathic Nephrotic Syndrome
Single-cell RNA-seq · human · 24 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 24 samples: 24 samples, each with a distinct title — no replicated groupsGroups 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 GSE305637_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 PRJNA1307400 and SRA study SRP609635. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 24 sample titles: 24 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.
- GSM9181230 scRNA-seq, P01, before RTX treatment
- GSM9181231 TCR-seq, P01, before RTX treatment
- GSM9181232 scRNA-seq, P01, after RTX treatment
- GSM9181233 TCR-seq, P01, after RTX treatment
- GSM9181234 scRNA-seq, P04, before RTX treatment
- GSM9181235 TCR-seq, P04, before RTX treatment
- GSM9181236 scRNA-seq, P04, after RTX treatment
- GSM9181237 TCR-seq, P04, after RTX treatment
- GSM9181238 scRNA-seq, P15, before RTX treatment
- GSM9181239 TCR-seq, P15, before RTX treatment
- GSM9181240 scRNA-seq, P15, after RTX treatment
- GSM9181241 TCR-seq, P15, after RTX treatment
- GSM9181242 scRNA-seq, P18, before RTX treatment
- GSM9181243 TCR-seq, P18, before RTX treatment
- GSM9181244 scRNA-seq, P18, after RTX treatment
- GSM9181245 TCR-seq, P18, after RTX treatment
- GSM9181246 scRNA-seq, P29, before RTX treatment
- GSM9181247 TCR-seq, P29, before RTX treatment
- GSM9181248 scRNA-seq, P29, after RTX treatment
- GSM9181249 TCR-seq, P29, after RTX treatment
- GSM9181250 scRNA-seq, P35, before RTX treatment
- GSM9181251 TCR-seq, P35, before RTX treatment
- GSM9181252 scRNA-seq, P35, after RTX treatment
- GSM9181253 TCR-seq, P35, after RTX treatment
- GSE314430 HDAC4 myonuclear reprogramming underlies denervation and weakness following musculoskeletal trauma 43 samples shares reprogramming, underlies
- GSE286923 Modularity of OCT4 underlies its functional diversity in reprogramming and embryonic development. 19 samples shares reprogramming, underlies
- GSE236589 Enhancer reprogramming underlies therapeutic utility of a SMARCA2 degrader in SMARCA4 mutant cancer [ChIP-Seq] 12 samples shares reprogramming, underlies
- GSE328224 Reprogramming CAR with cytokine signaling increases the efficacy of CAR-T cell therapy in solid tumour treatment and confers sustained immune memory 11 samples shares reprogramming, efficacy
- GSE310479 Targeting Fused in Sarcoma (FUS): A Novel Antisense Strategy for Treating Idiopathic Pulmonary Fibrosis 38 samples shares idiopathic
- GSE271896 Deep longitudinal immune profiling reveals reprogramming of memory T cells that links to B cell dysregulation with age 868 samples shares reprogramming
- GSE275067 Deep longitudinal immune profiling reveals reprogramming of memory T cells that links to B cell dysregulation with age. 252 samples shares reprogramming
- GSE215274 Identification of Whole Blood Gene Expression Signature to Predict the Therapeutic Effect of Nintedanib in Idiopathic Pulmonary Fibrosis 177 samples shares idiopathic
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.