Multiplexing droplet-based single cell RNA-sequencing using genetic barcodes
Here, we introduce an in-silico algorithm demuxlet that harnesses naturally occurring genetic variation in a pool of cells from unrelated individuals to discover the sample identity of each cell and identify droplets containing cells from two different individuals (doublets). These two capabilities enable a simple multiplexing design that increases single cell library construction throughput by experimental design where cells from genetically diverse samples are multiplexed and captured at 2-10x...
Provenance — who produced it, who reused it
Linked to 28 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- Integrating single-cell transcriptomic data across different con... 2018 · 14,641 cites
- Efficient integration of heterogeneous single-cell transcriptome... 2019 · 997 cites
- Confronting false discoveries in single-cell differential expres... 2021 · 980 cites
- Vireo: Bayesian demultiplexing of pooled single-cell RNA-seq dat... 2019 · 389 cites
- Functional interpretation of single cell similarity maps 2019 · 285 cites
- Cell type prioritization in single-cell data 2020 · 268 cites
- Jointly defining cell types from multiple single-cell datasets u... 2020 · 218 cites
- Benchmarking Computational Doublet-Detection Methods for Single-... 2020 · 218 cites
- DoubletDecon: Deconvoluting Doublets from Single-Cell RNA-Sequen... 2019 · 208 cites
- VEGA is an interpretable generative model for inferring biologic... 2021 · 106 cites
17 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.