The therapeutic mechanism of baritinib in idiopathic granulomatous mastitis treatment elucidated by single-cell RNA sequencing
Single-cell RNA-seq · human · 13 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 13 samples: 5 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 GSE274011_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 PRJNA1144462 and SRA study SRP524262. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 13 samples.
How we read this: 5 replicated groups read from 13 sample titles; they account for 13 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.
- GSM8441771 Micorwell-seq datasets of patient1_replicate1 Micorwell-seq datasets …
- GSM8477062 Micorwell-seq datasets of patient1_replicate2 Micorwell-seq datasets …
- GSM8477063 Micorwell-seq datasets of patient2_replicate1 Micorwell-seq datasets …
- GSM8477064 Micorwell-seq datasets of patient2_replicate2 Micorwell-seq datasets …
- GSM8477065 Micorwell-seq datasets of patient3_replicate1 Micorwell-seq datasets …
- GSM8477066 Micorwell-seq datasets of patient3_replicate2 Micorwell-seq datasets …
- GSM8477067 Micorwell-seq datasets of patient3_replicate3 Micorwell-seq datasets …
- GSM8477068 Micorwell-seq datasets of patient4_replicate1 Micorwell-seq datasets …
- GSM8477069 Micorwell-seq datasets of patient4_replicate2 Micorwell-seq datasets …
- GSM8477070 Micorwell-seq datasets of patient4_replicate3 Micorwell-seq datasets …
- GSM8477071 Micorwell-seq datasets of patient4_replicate4 Micorwell-seq datasets …
- GSM8477072 Micorwell-seq datasets of patient5_replicate1 Micorwell-seq datasets …
- GSM8477073 Micorwell-seq datasets of patient5_replicate2 Micorwell-seq datasets …
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- GSE280982 Single-cell sequencing across radiation treatment timepoints in head and neck cancer 49 samples shares single-cell, treatment
- GSE305971 Integrative single-cell analysis reveals malignant archetypes and proliferative hierarchies in multiple myeloma 2105 samples shares single-cell
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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.