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 # 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.
+Single-cell analysis is evolving from a niche area of interest into a well-established field of study. As a result, we are certainly not the first to produce a book on this subject, nor to provide guides and tutorials. In the sections that follow, we review two notable and ongoing initiatives aimed at teaching single-cell analysis, highlighting both their similarities to and differences from this book.
 
 ## Bioconductor OSCA and OSTA books
 
-Orchestrating Single-Cell Analysis with Bioconductor (Bioconductor OSCA){cite}`osca` accessible at https://bioconductor.org/books/release/OSCA/ is a digital book which aims to teach common workflows for the analysis of single-cell {term}`RNA`-Seq with the R based Bioconductor{cite}`pa:Huber2015` ecosystem. A paper with the same name{cite}`Amezquita2020` 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.
+Orchestrating Single-Cell Analysis with Bioconductor (Bioconductor OSCA) {cite}`osca`, available online at https://bioconductor.org/books/release/OSCA/, is a digital book designed to teach common workflows for analyzing of single-cell {term}`RNA`-Sequencing (scRNA-seq) data using the R based Bioconductor ecosystem {cite}`pa:Huber2015`. An accompanying paper with the same title {cite}`Amezquita2020`provides an overview of single-cell analysis with Bioconductor, while the online book offers more in-depth coverage, featuring detailed explanations and extensive code examples.
+
+The OSCA book is highly comprehensive in its treatment of basic scRNA-seq analysis, offering clear explanations and detailed workflow examples. However, it does not extend to other single-cell omics, such as single-cell ATAC-seq (scATAC-seq). Spatial transcriptomics is addressed separately in the complementary book Orchestrating Spatially-Resolved Transcriptomics Analysis with Bioconductor (Bioconductor OSTA), available at https://lmweber.org/OSTA-book/.
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+As both books are tailored to the Bioconductor ecosystem, they exclusively use tools available within Bioconductor. While these tools are highly effective, they may not always provide the most optimal solution for every analysis, as acknowledged by the books themselves. Overall, the Bioconductor books are particularly well-suited for individuals with a foundational knowledge of R and a strong background in biology who wish to learn how to analyze single-cell and spatial transcriptomics data within the Bioconductor framework.
 
 ## Current best practices in single-cell RNA-seq analysis: a tutorial
 
-Current best practices in single-cell {term}`RNA`-seq analysis: a tutorial{cite}`pa:Lücken2019` is a paper written by Malte Lücken and Fabian Theis which introduces best practice single-cell {term}`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](https://github.com/theislab/single-cell-tutorial/) from Haber et al. {cite}`pa:Haber2017`.
+Current Best Practices in Single-Cell {term}`RNA`-Seq Analysis: A Tutorial {cite}`pa:Lücken2019` by Malte Lücken and Fabian Theis is a paper that introduces best practices for scRNA-seq analysis. Its key contribution lies in not only reviewing potential analysis steps but also recommending best practices based on independent benchmarks. When specific best-practice guidelines are unavailable, the authors provide general recommendations for analysis approaches. The paper is complemented by an [example analysis of mouse intestinal epithelium regions](https://github.com/theislab/single-cell-tutorial/) from Haber et al. {cite}`pa:Haber2017`.
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+In comparison to Bioconductor OSCA, this paper and its associated analysis are not constrained by a specific tool ecosystem, offering a broader perspective on the range of topics covered. However, the accompanying example analysis lacks beginner-friendliness and has become somewhat outdated. Like Bioconductor OSCA, this paper does not address newer developments such as RNA velocity, spatial transcriptomics, or multi-omics.
 
-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.
+Despite these limitations, we highly recommend this paper as a valuable introduction to the field and as a guide to initial best practices in scRNA-seq analysis. The chapters in this book build on the latest best practices, offering an updated perspective on the field. Furthermore, the workflows in this book are explained in greater detail, providing readers with the background information necessary to effectively apply the methods. We advise against relying on the example case study provided with the paper and instead encourage readers to explore the detailed chapters in this book for a more comprehensive and modern understanding.
 
 ## References