Transcriptome-scale RNA-targeting CRISPR screens reveal essential lncRNAs in human cells
Single-cell RNA-seq · human · 12 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
- 12 samples: 11 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
- RETRACTED: Transcriptome-scale RNA-targeting CRISPR screens reveal essential lncRNAs in human cellsCell · 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 GSE281460_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 PRJNA1161603 and SRA study SRP543663. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 12 sample titles: 11 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.
- GSM8621112 RfxCas13d expressing THP1 cells, pooled lncRNA library, before dox induction, reps 1 and 2
- GSM8621113 RfxCas13d expressing MDA-MB-231 cells, pooled lncRNA library, 14 days after dox induction, reps 1 and 2
- GSM8621114 RfxCas13d expressing MDA-MB-231 cells, pooled lncRNA library, 7 days after dox induction, reps 1 and 2
- GSM8621115 RfxCas13d expressing MDA-MB-231 cells, pooled lncRNA library, before dox induction, reps 1 and 2
- GSM8621116 RfxCas13d expressing K562 cells, pooled lncRNA library, before, 7 days after, or 14 days after dox induction, rep2
- GSM8621117 RfxCas13d expressing K562 cells, pooled lncRNA library, before, 7 days after, or 14 days after dox induction, rep1
- GSM8621118 RfxCas13d expressing HEK293FT cells, pooled lncRNA library, 7 or 14 days after dox induction, rep1 or 2
- GSM8621119 RfxCas13d expressing HEK293FT cells, pooled lncRNA library, before or 7 days after dox induction, rep1 or 2
- GSM8621120 RfxCas13d expressing THP1 cells, pooled lncRNA library, 14 days after dox induction, reps 1 and 2
- GSM8621121 RfxCas13d expressing THP1 cells, pooled lncRNA library, 7 days after dox induction, reps 1 and 2
- GSM8621122 RfxCas13d expressing HAP1 cells, pooled lncRNA library, 7 or 14 days after dox induction, rep1 or 2
- GSM8621123 RfxCas13d expressing HAP1 cells, pooled lncRNA library, before or 7 days after dox induction, rep1 or 2
- GSE326978 Essential lncRNAs in the human transcriptome [CRISPR] 16 samples shares crispr, essential, lncrnas
- GSE330227 In vivo genome-wide CRISPR screens in human T cells to enhance T cell therapy for solid tumors 30 samples shares crispr, screens
- GSE224986 Single-cell CRISPRi screens of breast cancer associated enhancers 94 samples shares crispr, screens
- GSE300879 Identification of replicative aging and inflammatory aging signatures via whole-genome CRISPRi screens 16 samples shares crispr, screens
- GSE305958 CRISPR Screens Identify the ATPase VCP as a Druggable Therapeutic Vulnerability in Cholangiocarcinoma 14 samples shares crispr, screens
- GSE245239 CRISPR activation screens identify the SWI-SNF ATPases as suppressors of ferroptosis [NGS3752_RNA] 12 samples shares crispr, screens
- GSE272093 CRISPRi-based screens in iAssembloids to elucidate neuron-glia interactions 10 samples shares crispr, screens
- GSE243457 Identifying human pre-mRNA cleavage and polyadenylation factors by genome-wide CRISPR screens in a dual fluorescence readthrough reporter 28 samples shares crispr, screens
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.