Single-Cell Cas12a Platform for Screening and CRISPRi
Single-cell RNA-seq · human · 26 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
- 26 samples: 26 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.
- Paper
- A tunable Cas12a platform for single-cell perturbation screening and CRISPRiNature communications · 2026
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 GSE283574_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 PRJNA1194560 and SRA study SRP549602. 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 26 sample titles: 26 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.
- GSM8666563 H358Cas12a_CellSurfaceReceptors_CROPseq_FL
- GSM8666564 H358Cas12a_CellSurfaceReceptors_DCCROPseq_FL
- GSM8666565 H358Cas12a_CellSurfaceReceptors_DCPerturbseq_FL
- GSM8666566 H358_CellSurfaceReceptors_CROPseq_FL
- GSM8666567 H358_CellSurfaceReceptors_DCCROPseq_FL
- GSM8666568 H358_CellSurfaceReceptors_DCPerturbseq_FL
- GSM8666569 H358Cas12a_EpiGenFactor_CROPseq_BC
- GSM8666570 H358Cas12a_EpiGenFactor_CROPseq_FL
- GSM8666571 H358Cas12a_EpiGenFactor_DCPerturbseq_BC
- GSM8666572 H358Cas12a_EpiGenFactor_DCPerturbseq_FL
- GSM8666573 H358Cas12a_EpiGenFactor_DCPerturbseq_GEX
- GSM8666574 H358Cas12a_EpiGenFactor_GEX
- GSM8666575 H358Cas12adTagV124h_EpiGenFactor_CROPseq_BC
- GSM8666576 H358Cas12adTagV124h_EpiGenFactor_GEX
- GSM8666577 H358Cas12adTagV124h_EpiGenFactor_HTO
- GSM8666578 H358Cas12adTagV148h_CellSurfaceReceptors_DCPerturbseq_FL
- GSM8666579 H358Cas12adTagV148h_CellSurfaceReceptors_GEX
- GSM8666580 H358Cas12adTagV148h_CellSurfaceReceptors_HTO
- GSM8666581 H358Cas12adTagV148h_EpiGenFactor_CROPseq_BC
- GSM8666582 H358Cas12adTagV148h_EpiGenFactor_GEX
- GSM8666583 H358Cas12adTagV148h_EpiGenFactor_HTO
- GSM8666584 H358Cas12adTagV124h_EpiGenFactor_CROPseq_FL
- GSM8666585 H358Cas12adTagV148h_CellSurfaceReceptors_CROPseq_FL
- GSM8666586 H358Cas12adTagV148h_EpiGenFactor_CROPseq_FL
- GSM8666587 K562Cas12a_BC
- GSM8666588 K562Cas12a_HTO
- GSE305971 Integrative single-cell analysis reveals malignant archetypes and proliferative hierarchies in multiple myeloma 2105 samples shares single-cell
- GSE243013 A single-cell atlas of immune heterogeneity in anti-PD1-treated non-small cell lung cancer 243 samples shares single-cell
- GSE263733 Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications 218 samples shares single-cell
- GSE282122 A longitudinal single-cell atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease 216 samples shares single-cell
- GSE328048 Single-cell transcriptome reveals keratinocyte subclusters that contribute to altered differentiation and inflammatory responses in atopic dermatitis 116 samples shares single-cell
- GSE327167 Single-cell RNA-seq profiling of pleural mesothelioma and comparator pleural specimens 113 samples shares single-cell
- GSE266265 Endometrial Insights: Unmasking Endometriosis through Single-Cell Profiling and AI-Based Prediction 60 samples shares single-cell
- GSE287301 Single-cell RNA-sequencing of HNSCC-infiltrating T cells 48 samples shares single-cell
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.