Modular, efficient and constant-memory single-cell RNA-seq preprocessing
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 wo...
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| Veröffentlicht in: | Nature biotechnology 2021-07, Vol.39 (7), p.813-818 |
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| container_title | Nature biotechnology |
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| creator | Melsted, Páll Booeshaghi, A. Sina Liu, Lauren Gao, Fan Lu, Lambda Min, Kyung Hoi (Joseph) da Veiga Beltrame, Eduardo Hjörleifsson, Kristján Eldjárn Gehring, Jase Pachter, Lior |
| description | 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.
A preprocessing workflow for single-cell RNA-seq data achieves near-optimal speed. |
| doi_str_mv | 10.1038/s41587-021-00870-2 |
| format | Article |
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The workflow is modular, and we demonstrate its flexibility by showing how it can be used for RNA velocity analyses.
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| subjects | 631/114/2785 631/114/794 631/61/212/2019 Agriculture Analysis Base Sequence Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Computer engineering Computer science Datasets Efficiency Experiments Gene sequencing Genes Genetic engineering Genetic markers Genomics High-Throughput Nucleotide Sequencing Humans Identification and classification Letter Life Sciences Mechanical engineering Methods Preprocessing Ribonucleic acid RNA RNA sequencing Sequence Analysis, RNA Single-Cell Analysis Software Workflow |
| title | Modular, efficient and constant-memory single-cell RNA-seq preprocessing |
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