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OP3: single-cell multimodal dataset in PBMCs for perturbation prediction benchmarking

GSE279945 Homo sapiens (human) Single-cell RNA-seq 102 samples Submitted 2024/10/22 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 102 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
102 samples: 6 conditions, mostly with about 16 replicates eachGroups 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.
Summary (written by the submitters)
The Open Problems Perurbation Prediction (OP3) dataset is to-date the largest single-cell small molecule perturbation dataset in primary tissue with multiple donor replicates. Compounds are dosed in cultured peripheral blood mononuclear cells (PBMCs), enabling the robust computation of perturbation effects on gene expression across four distinct cell type populations: T-cells, B-cells, NK cells, and Myeloid cells. This dataset is the basis for the OP3 benchmark, which evaluates machine learning models on the task of extrapolation perturbation effects into unseen cell types.
This dataset
Open GSE279945 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE279945_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1149320 and SRA study SRP527159. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 16 replicates each
Donor 1, hashed perturbation sample ×16 Donor 1, hashtags for perturbation sample ×16 Donor 2, hashed perturbation sample ×16 Donor 2, hashtags for perturbation sample ×16 Donor 3, hashed perturbation sample ×16 Donor 3, hashtags for perturbation sample ×16 Donor 1, baseline multiome gene expression ×1 Donor 1, baseline multiome chromatin accessib… ×1 +4 more

Supports a between-group comparison across 96 samples.

How we read this: 6 replicated groups read from 102 sample titles; they account for 96 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.

Samples in this study

+ 62 more — browse all 102 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.