Virus-like particles enable targeted gene engineering and pooled CRISPR screening in primary human myeloid cells [RNA-seq Exp2]
RNA-seq (gene expression) · human · 12 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 12 samples: 12 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.
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 GSE327352_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1450562 and SRA study SRP690175. 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 12 sample titles: 12 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.
- GSM9654214 Donor 1, EDV treated, no additional stimulation
- GSM9654215 Donor 1, EDV treated, stimulated with LPS + Interferon gamma
- GSM9654216 Donor 1, no Cas9, no additional stimulation
- GSM9654217 Donor 1, no Cas9, stimulated with LPS + Interferon gamma
- GSM9654218 Donor 1, Cas9-RNP nucleofection, no additional stimulation
- GSM9654219 Donor 1, Cas9-RNP nucleofection, stimulated with LPS + Interferon gamma
- GSM9654220 Donor 2, EDV treated, no additional stimulation
- GSM9654221 Donor 2, EDV treated, stimulated with LPS + Interferon gamma
- GSM9654222 Donor 2, no Cas9, no additional stimulation
- GSM9654223 Donor 2, no Cas9, stimulated with LPS + Interferon gamma
- GSM9654224 Donor 2, Cas9-RNP nucleofection, no additional stimulation
- GSM9654225 Donor 2, Cas9-RNP nucleofection, stimulated with LPS + Interferon gamma
- GSE327133 Virus-like particles enable targeted gene engineering and pooled CRISPR screening in primary human myeloid cells [CRISPRoff] 28 samples shares crispr, engineering, virus-like, particles, screening, targeted, primary
- GSE327354 Virus-like particles enable targeted gene engineering and pooled CRISPR screening in primary human myeloid cells [RNA-seq Exp3] 18 samples shares crispr, engineering, virus-like, particles, screening, targeted, primary
- GSE327357 Virus-like particles enable targeted gene engineering and pooled CRISPR screening in primary human myeloid cells [RNA-Seq Exp1] 14 samples shares crispr, engineering, virus-like, particles, screening, targeted, primary
- GSE327424 Virus-like particles enable targeted gene engineering and pooled CRISPR screening in primary human myeloid cells 86 samples shares crispr, engineering, virus-like, particles, screening, targeted, primary
- GSE318716 In vivo engineering of hematopoietic stem cells by targeted lipid nanoparticles within humanized mice 21 samples shares engineering, particles, targeted
- GSE301632 Genome-wide CRISPR-Cas9 knockout screening identifies NUDCD2 depletion as sensitizer for bortezomib, carfilzomib and ixazomib in multiple myeloma. 27 samples shares crispr, screening
- GSE283574 Single-Cell Cas12a Platform for Screening and CRISPRi 26 samples shares crispr, screening
- GSE303100 Dissecting Resistance to CDK4/6 Inhibition in Experimental Glioma via Genome-wide CRISPR-Cas9 Screening 24 samples shares crispr, screening
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.