1. Prior art#

Single-cell analysis is slowly transitioning from an interesting niche topic to a more mature field. Hence, we are arguably not the first to write a book on single-cell analysis, let alone guides and tutorials. In the following sections, we highlight two existing and ongoing efforts to teach single-cell analysis and emphasize commonalities and differences to this book.

1.1. Bioconductor OSCA and OSTA books#

Orchestrating Single-Cell Analysis with Bioconductor (Bioconductor OSCA)[Amezquita et al., 2022] accessible at https://bioconductor.org/books/release/OSCA/ is a digital book which aims to teach common workflows for the analysis of single-cell RNA-Seq with the R based Bioconductor[Huber et al., 2015] ecosystem. A paper with the same name[Amezquita et al., 2020] presented an overview of single-cell analysis with Bioconductor and the book is an associated online version which goes into greater detail with extensive code examples. The book is very comprehensive with respect to basic single-cell RNA-Seq analysis with great explanations and extensive workflow examples. However, it does not comprise other single-cell omics such as scATAC-seq. Spatial transcriptomics is covered in the complementary Orchestrating Spatially-Resolved Transcriptomics Analysis with Bioconductor (Bioconductor OSTA) book (https://lmweber.org/OSTA-book/). Since the books are designed for the Bioconductor ecosystem they only employ tools available on Bioconductor. These do not necessarily result in an optimal analysis as denoted in the books themselves. We perceive the Bioconductor books as especially useful for people with a basic R and stronger biology background who are interested in learning how to analyze single-cell and spatial transcriptomics data analysis with Bioconductor.

1.2. Current best practices in single-cell RNA-seq analysis: a tutorial#

Current best practices in single-cell RNA-seq analysis: a tutorial[Luecken and Theis, 2019] is a paper written by Malte Lücken and Fabian Theis which introduces best practice single-cell RNA-Seq analysis. The unique contribution of the paper to the field is that it not only serves as a review of the possible analysis steps, but always suggests best practices based on independent benchmarks. Whenever recommendations for best practices are not available, general recommendations for analysis approaches are suggested. The paper itself is accompanied with an example analysis of mouse intestinal epithelium regions from Haber et al. [Haber et al., 2017].

Compared to Bioconductor OSCA, the paper and the example analysis is not biased by the tools that it showcases and more complete in content with respect to the breadth of covered topics. Nevertheless, the associated example analysis lacks in newbie friendliness and has already become outdated. Moreover, similarly to the Bioconductor OSCA paper and book, Lücken and Theis do not cover more recent topics such as RNA velocity, spatial transcriptomics or multi-omics. We strongly recommend the paper as an introduction and overview to the field and initial analysis best-practice recommendations. The chapters in this book are based on the most recent best practices and provide an updated view on the field. Additionally, the analysis workflows in this book are explained in much more detail to provide readers more background information needed to run the methods. We generally advise against examining the associated case-study and suggest to instead read the chapters of this book in detail.

1.3. References#


Robert Amezquita, Aaron Lun, Stephanie Hicks, and Gottardo Raphael. Orchestrating single-cell analysis with bioconductor. https://bioconductor.org/books/release/OSCA/, 2022. Accessed: 2022-04-21.


Robert A. Amezquita, Aaron T. L. Lun, Etienne Becht, Vince J. Carey, Lindsay N. Carpp, Ludwig Geistlinger, Federico Marini, Kevin Rue-Albrecht, Davide Risso, Charlotte Soneson, Levi Waldron, Hervé Pagès, Mike L. Smith, Wolfgang Huber, Martin Morgan, Raphael Gottardo, and Stephanie C. Hicks. Orchestrating single-cell analysis with bioconductor. Nature Methods, 17(2):137–145, Feb 2020. URL: https://doi.org/10.1038/s41592-019-0654-x, doi:10.1038/s41592-019-0654-x.


Adam L. Haber, Moshe Biton, Noga Rogel, Rebecca H. Herbst, Karthik Shekhar, Christopher Smillie, Grace Burgin, Toni M. Delorey, Michael R. Howitt, Yarden Katz, Itay Tirosh, Semir Beyaz, Danielle Dionne, Mei Zhang, Raktima Raychowdhury, Wendy S. Garrett, Orit Rozenblatt-Rosen, Hai Ning Shi, Omer Yilmaz, Ramnik J. Xavier, and Aviv Regev. A single-cell survey of the small intestinal epithelium. Nature, 551(7680):333–339, Nov 2017. URL: https://doi.org/10.1038/nature24489, doi:10.1038/nature24489.


Wolfgang Huber, Vincent J. Carey, Robert Gentleman, Simon Anders, Marc Carlson, Benilton S. Carvalho, Hector Corrada Bravo, Sean Davis, Laurent Gatto, Thomas Girke, Raphael Gottardo, Florian Hahne, Kasper D. Hansen, Rafael A. Irizarry, Michael Lawrence, Michael I. Love, James MacDonald, Valerie Obenchain, Andrzej K. Oleś, Hervé Pagès, Alejandro Reyes, Paul Shannon, Gordon K. Smyth, Dan Tenenbaum, Levi Waldron, and Martin Morgan. Orchestrating high-throughput genomic analysis with bioconductor. Nature Methods, 12(2):115–121, Feb 2015. URL: https://doi.org/10.1038/nmeth.3252, doi:10.1038/nmeth.3252.


Malte D Luecken and Fabian J Theis. Current best practices in single-cell term`rna`-seq analysis: a tutorial. Molecular Systems Biology, 15(6):e8746, 2019. URL: https://www.embopress.org/doi/abs/10.15252/msb.20188746, arXiv:https://www.embopress.org/doi/pdf/10.15252/msb.20188746, doi:https://doi.org/10.15252/msb.20188746.