ArticleNature biotechnology2021
Modular, efficient and constant-memory single-cell RNA-seq preprocessing.
Article in Nature biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 251 papers.
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Who cites it
251 citing papers in PubMed.
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- The immunophenotype and proviral landscape of HIV-infected CD4 T cells during antiretroviral therapy.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A massively parallel CRISPR-based screening platform for modifiers of neuronal depolarization.Nature communications · 2026Article
- A rare pre-existing progenitor-like Primed SMC compartment is the dominant inferred source of SMC-derived cellularity in vascular injury and atherosclerosis.bioRxiv : the preprint server for biology · 2026Article
- Hybrid crosses reveal a cell-type-specific landscape of mouse regulatory variation.bioRxiv : the preprint server for biology · 2026Article
- A tunable Cas12a platform for single-cell perturbation screening and CRISPRi.Nature communications · 2026Article
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- Targeted single-cell RNA and perturbation sequencing with TAP-seq.Nature protocols · 2026Review
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- Robust identification of cell-cell communication heterogeneity in single cells.bioRxiv : the preprint server for biology · 2026Article
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- Single-cell epigenetic and transcriptomic states across the continuum of monoclonal B cell lymphocytosis to chronic lymphocytic leukemia.Genome biology · 2026Article
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- Systematic cell-type resolved transcriptomes of 8 tissues in 8 lab and wild-derived mouse strains capture global and local expression variation.Cell genomics · 2026Article
- Single-cell RNA-seq reveals trans-sialidase-like superfamily gene expression heterogeneity ineLife · 2026Article
- Dissecting PGENature communications · 2026Article
191 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
We describe a workflow for preprocessing of single-cell RNA-sequencing data that balances efficiency and accuracy. Our workflow is based on the kallisto and bustools programs, and is near optimal in speed with a constant memory requirement providing scalability for arbitrarily large datasets. The workflow is modular, and we demonstrate its flexibility by showing how it can be used for RNA velocity analyses.
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