Melsted, P. et al. Modular, efficient and constant-memory single-cell RNA-seq preprocessing. Nat. Biotechnol. 39, 813–818 (2021).

Article  CAS  PubMed  Google Scholar 

Tian, L. et al. scPipe: a flexible R/Bioconductor preprocessing pipeline for single-cell RNA-sequencing data. PLoS Comput. Biol. 14, e1006361 (2018).

Article  PubMed  PubMed Central  Google Scholar 

Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat. Methods 5, 621–628 (2008).

Article  CAS  PubMed  Google Scholar 

Conesa, A. et al. A survey of best practices for RNA-seq data analysis. Genome Biol. 17, 13 (2016).

Article  PubMed  PubMed Central  Google Scholar 

Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

Article  CAS  PubMed  Google Scholar 

Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578 (2012).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Roberts, A. & Pachter, L. Streaming fragment assignment for real-time analysis of sequencing experiments. Nat. Methods 10, 71–73 (2013).

Article  CAS  PubMed  Google Scholar 

Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).

Article  CAS  PubMed  Google Scholar 

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Liao, Y., Smyth, G. K. & Shi, W. The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads. Nucleic Acids Res. 47, e47 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

Article  CAS  PubMed  Google Scholar 

Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

Article  CAS  PubMed  Google Scholar 

Pertea, M., Kim, D., Pertea, G. M., Leek, J. T. & Salzberg, S. L. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat. Protoc. 11, 1650–1667 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinforma. 12, 323 (2011).

Article  CAS  Google Scholar 

Srivastava, A., Malik, L., Smith, T., Sudbery, I. & Patro, R. Alevin efficiently estimates accurate gene abundances from dscRNA-seq data. Genome Biol. 20, 65 (2019).

Article  PubMed  PubMed Central  Google Scholar 

He, D. et al. Alevin-fry unlocks rapid, accurate and memory-frugal quantification of single-cell RNA-seq data. Nat. Methods 19, 316–322 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

He, D. & Patro, R. simpleaf: a simple, flexible, and scalable framework for single-cell data processing using alevin-fry. Bioinformatics https://doi.org/10.1093/bioinformatics/btad614 (2023).

Kaminow, B., Yunusov, D. & Dobin, A. STARsolo: accurate, fast and versatile mapping/quantification of single-cell and single-nucleus RNA-seq data. Preprint at bioRxiv https://doi.org/10.1101/2021.05.05.442755 (2021).

Niebler, S., Müller, A., Hankeln, T. & Schmidt, B. RainDrop: rapid activation matrix computation for droplet-based single-cell RNA-seq reads. BMC Bioinforma. 21, 274 (2020).

Article  CAS  Google Scholar 

Liao, Y., Raghu, D., Pal, B., Mielke, L. A. & Shi, W. cellCounts: an R function for quantifying 10x Chromium single-cell RNA sequencing data. Bioinformatics https://doi.org/10.1093/bioinformatics/btad439 (2023).

Battenberg, K. et al. A flexible cross-platform single-cell data processing pipeline. Nat. Commun. 13, 6847 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Melsted, P., Ntranos, V. & Pachter, L. The barcode, UMI, set format and BUStools. Bioinformatics 35, 4472–4473 (2019).

Article  CAS  PubMed  Google Scholar 

Hjörleifsson, K. E. et al. Accurate quantification of single-cell and single-nucleus RNA-seq transcripts using distinguishing flanking k-mers. Preprint at bioRxiv https://doi.org/10.1101/2022.12.02.518832 (2024).

Kivioja, T. et al. Counting absolute numbers of molecules using unique molecular identifiers. Nat. Methods 9, 72–74 (2011).

Article  PubMed  Google Scholar 

Smith, T., Heger, A. & Sudbery, I. UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy. Genome Res. 27, 491–499 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Reese, M. G. et al. Genome annotation assessment in Drosophila melanogaster. Genome Res. 10, 483–501 (2000).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kent, W. J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Booeshaghi, A. S., Min, K. H. J., Gehring, J. & Pachter, L. Quantifying orthogonal barcodes for sequence census assays. Bioinf. Adv 4, 1 (2024).

Google Scholar 

Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Booeshaghi, A. S., Gao, F. & Pachter, L. Assessing the multimodal tradeoff. Preprint at bioRxiv https://doi.org/10.1101/2021.12.08.471788 (2023).

Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Luebbert, L. et al. Efficient and accurate detection of viral sequences at single-cell resolution reveals putative novel viruses perturbing host gene expression. Preprint at bioRxiv https://doi.org/10.1101/2023.12.11.571168 (2024).

Holley, G. & Melsted, P. Bifrost: highly parallel construction and indexing of colored and compacted de Bruijn graphs. Genome Biol. 21, 249 (2020).

Article  PubMed  PubMed Central  Google Scholar 

Iqbal, Z., Caccamo, M., Turner, I., Flicek, P. & McVean, G. De novo assembly and genotyping of variants using colored de Bruijn graphs. Nat. Genet. 44, 226–232 (2012).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Martin, F. J. et al. Ensembl 2023. Nucleic Acids Res. 51, D933–D941 (2023).

Grindberg, R. V. et al. RNA-sequencing from single nuclei. Proc. Natl Acad. Sci. USA 110, 19802–19807 (2013).

Article  CAS  PubMed  PubMed Central  Google Scholar 

La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).

Article