References

10xGenomics. 2019. “Single-Cell RNA-Seq: An Introductory Overview and Tools for Getting Started. Retrieved 06-08-2019. https://community.10xgenomics.com/t5/10x-Blog/Single-Cell-RNA-Seq-An-Introductory-Overview-and-Tools-for/ba-p/547.” 10xGenomics, 5–9. https://www.10xgenomics.com/blog/single-cell-rna-seq-an-introductory-overview-and-tools-for-getting-started.

Anders, Simon. 2010. “Babraham Bioinformatics - FastQC A Quality Control tool for High Throughput Sequence Data.” https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.

Andrews, Tallulah S., and Martin Hemberg. 2018. “False signals induced by single-cell imputation.” F1000Research 7: 1740. https://doi.org/10.12688/f1000research.16613.1.

Argelaguet, Ricard, Denis Arnol, Dmitry Bredikhin, Yann Deloro, Benedikt Velten, John C. Marioni, and Oliver Stegle. 2020. “MOFA+: A Statistical Framework for Comprehensive Integration of Multi-Modal Single-Cell Data.” Genome Biology 21: 111. https://doi.org/10.1186/s13059-020-02015-1.

Ashuach, Tal, Mariano Gabitto, Michael I Jordan, and Nir Yosef. 2021. “MultiVI: Deep Generative Model for the Integration of Multi-Modal Data.” bioRxiv. https://doi.org/10.1101/2021.08.20.457057.

Bray, Nicolas L., Harold Pimentel, Páll Melsted, and Lior Pachter. 2016. “Near-optimal probabilistic RNA-seq quantification.” Nature Biotechnology 34 (5): 525–27. https://doi.org/10.1038/nbt.3519.

Dijk, David van, Roshan Sharma, Juozas Nainys, Kristina Yim, Pooja Kathail, Ambrose J. Carr, Cassandra Burdziak, et al. 2018. “Recovering Gene Interactions from Single-Cell Data Using Data Diffusion.” Cell 174 (3): 716–729.e27. https://doi.org/10.1016/j.cell.2018.05.061.

Dobin, Alexander, Carrie A. Davis, Felix Schlesinger, Jorg Drenkow, Chris Zaleski, Sonali Jha, Philippe Batut, Mark Chaisson, and Thomas R. Gingeras. 2013. “STAR: Ultrafast universal RNA-seq aligner.” Bioinformatics 29 (1): 15–21. https://doi.org/10.1093/bioinformatics/bts635.

Eding, Matt. 2009. “Sparse Matrices.” In, 419–44. https://doi.org/10.1201/9781439811481.ch20.

Hafemeister, Christoph, and Rahul Satija. 2019. “Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression.” Genome Biology 20 (1): 1–15. https://doi.org/10.1186/S13059-019-1874-1/FIGURES/6.

Hao, Yuhan, Stephanie Hao, Erin Andersen-Nissen, et al. 2022. “Bridge Integration of Single-Cell Multi-Omics Data with Dictionary Learning.” bioRxiv. https://doi.org/10.1101/2022.02.24.481684.

Hao, Yuhan, Stephanie Hao, Erin Andersen-Nissen, William M Mauck III, Shiwei Zheng, Andrew Butler, Madison J Lee, et al. 2021. “Integrated Analysis of Multimodal Single-Cell Data.” Cell 184 (13): 3573–3587.e29. https://doi.org/10.1016/j.cell.2021.04.048.

Kang, Hyun Min, Manasa Subramaniam, Sheila Targ, Mai Nguyen, Lenka Maliskova, Erin McCarthy, Emily Wan, et al. 2018. “Multiplexed Droplet Single-Cell RNA-Sequencing Using Natural Genetic Variation.” Nature Biotechnology 36 (1): 89–94. https://doi.org/10.1038/nbt.4042.

Kharchenko, Peter V, Lev Silberstein, and David T Scadden. 2014. “Bayesian Approach to Single-Cell Differential Expression Analysis.” Nature Methods 11: 740–42. https://doi.org/10.1038/nmeth.2967.

Lun, Aaron, Samantha Riesenfeld, Tallulah Andrews, The Dao, Tomas Gomes, and John Marioni. 2019. “EmptyDrops: Distinguishing Cells from Empty Droplets in Droplet-Based Single-Cell RNA Sequencing Data.” Genome Biology 20 (March): 63. https://doi.org/10.1186/s13059-019-1662-y.

Macosko, Evan Z., Anindita Basu, Rahul Satija, James Nemesh, Karthik Shekhar, Melissa Goldman, Itay Tirosh, et al. 2015. “Highly Parallel Genome-Wide Expression Profiling of Individual Cells Using Nanoliter Droplets.” Cell 161 (5): 1202–14. https://doi.org/https://doi.org/10.1016/j.cell.2015.05.002.

McGinnis, Christopher S, Lauren M Murrow, and Zev J Gartner. 2019. “DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors.” Cell Systems 8 (4): 329–337.e4. https://doi.org/10.1016/j.cels.2019.03.003.

“Method of the Year 2013.” 2014. Nature Publishing Group. https://doi.org/10.1038/nmeth.2801.

Mistry, M. Freeman, B. Piper, M. 2017. “Alignment with STAR | Introduction to RNA-Seq using high-performance computing.” https://hbctraining.github.io/Intro-to-rnaseq-hpc-O2/lessons/03_alignment.html.

Stuart, Tim, Andrew Butler, Paul Hoffman, Christoph Hafemeister, Efthymia Papalexi, William M Mauck III, Yuhan Hao, Marlon Stoeckius, Peter Smibert, and Rahul Satija. 2019. “Comprehensive Integration of Single-Cell Data.” Cell 177 (7): 1888–1902.e21. https://doi.org/10.1016/j.cell.2019.05.031.

Svensson, Valentine, Roser Vento-Tormo, and Sarah A. Teichmann. 2018. “Exponential scaling of single-cell RNA-seq in the past decade.” Nature Publishing Group. https://doi.org/10.1038/nprot.2017.149.

Welch, Joshua D, Vanja Kozareva, Arthur Ferreira, Caleb Vanderburg, Craig Martin, and Evan Z Macosko. 2019. “Single-Cell Multi-Omic Integration Compares and Contrasts Features of Brain Cell Identity.” Cell 177 (7): 1873–1887.e17. https://doi.org/10.1016/j.cell.2019.05.006.

Wolock, Samuel L, Ramon Lopez, and Allon M Klein. 2019. “Scrublet: Computational Identification of Cell Doublets in Single-Cell Transcriptomic Data.” Cell Systems 8 (4): 281–291.e9. https://doi.org/10.1016/j.cels.2018.11.005.

Zhang, Xiannian, Tianqi Li, Feng Liu, Yaqi Chen, Jiacheng Yao, Zeyao Li, Yanyi Huang, and Jianbin Wang. 2018. “Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems.” Molecular Cell 73 (November). https://doi.org/10.1016/j.molcel.2018.10.020.

Zheng, Grace, Jessica Terry, Phillip Belgrader, Paul Ryvkin, Zachary Bent, Ryan Wilson, Solongo Ziraldo, et al. 2017. “Massively Parallel Digital Transcriptional Profiling of Single Cells.” Nature Communications 8 (January): 14049. https://doi.org/10.1038/ncomms14049.