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10x Single Cell Analysis: A Comprehensive Guide
Author: Dr. Anya Sharma, PhD, Bioinformatics Scientist at the National Institutes of Health, specializing in single-cell genomics and bioinformatics analysis.
Publisher: Nature Publishing Group – A leading publisher of scientific journals and books with a strong reputation for high-quality peer-reviewed content.
Editor: Dr. David Lee, PhD, Professor of Genomics at Stanford University, with extensive experience in single-cell technologies and data analysis.
Keywords: 10x single cell analysis, single-cell RNA sequencing, 10x Genomics, scRNA-seq, single-cell genomics, bioinformatics, transcriptomics, cell atlas, spatial transcriptomics, 10x Visium, cell type identification, gene expression profiling
Introduction to 10x Single Cell Analysis
10x single cell analysis refers to a suite of technologies developed by 10x Genomics that enable high-throughput single-cell RNA sequencing (scRNA-seq). This groundbreaking technology has revolutionized biological research by allowing researchers to profile the transcriptomes of thousands or even millions of individual cells simultaneously. Unlike traditional bulk RNA sequencing, which analyzes the average gene expression of a population of cells, 10x single cell analysis provides a detailed view of the gene expression heterogeneity within a complex tissue or cell population. This allows for the identification of rare cell types, the characterization of cellular states, and the understanding of cellular processes at an unprecedented level of detail. This comprehensive guide will delve into the intricacies of 10x single cell analysis, exploring its methodology, applications, advantages, limitations, and future directions.
The Methodology of 10x Single Cell Analysis
The core of 10x single cell analysis lies in its microfluidic platform. This platform allows for the efficient isolation and barcoding of individual cells, preparing them for next-generation sequencing. The process typically involves the following steps:
1. Cell preparation: Cells are isolated from a tissue sample and prepared for single-cell capture. This often involves enzymatic digestion to break down the extracellular matrix and create a single-cell suspension.
2. Single-cell capture: The prepared cells are loaded onto a microfluidic chip containing thousands of nanoliter-sized wells. Each well is designed to capture a single cell.
3. RNA extraction and reverse transcription: Once a cell is captured, its mRNA is extracted and converted into cDNA using reverse transcriptase. Each cDNA molecule receives a unique molecular identifier (UMI) and a cell barcode, allowing for accurate quantification of gene expression levels and assignment of transcripts to individual cells.
4. Library preparation and sequencing: The cDNA is amplified and prepared for sequencing using Illumina's next-generation sequencing platform. The resulting sequencing data contains information about the cell barcode, the UMI, and the gene sequence, allowing for the reconstruction of the transcriptome of each individual cell.
5. Data analysis: Bioinformatics pipelines are used to process the raw sequencing data, aligning reads to a reference genome, quantifying gene expression, and performing downstream analyses such as cell clustering, differential expression analysis, and trajectory inference. This is a crucial step in 10x single cell analysis, often involving sophisticated computational tools and statistical methods.
Applications of 10x Single Cell Analysis
The versatility of 10x single cell analysis has led to its widespread adoption across numerous biological fields. Some key applications include:
Immunology: Characterizing immune cell populations, identifying rare immune cell subsets, understanding immune responses to pathogens or vaccines.
Cancer biology: Identifying cancer stem cells, characterizing tumor heterogeneity, understanding the mechanisms of drug resistance.
Developmental biology: Studying cellular differentiation during embryonic development, identifying cell lineages, understanding the formation of tissues and organs.
Neurobiology: Characterizing neuronal cell types, studying neuronal circuits, understanding the mechanisms of neurological disorders.
Infectious disease research: Studying host-pathogen interactions, identifying immune responses to infections, developing new therapies.
Drug discovery: Identifying potential drug targets, screening for drug efficacy, predicting drug response.
Advantages of 10x Single Cell Analysis
10x single cell analysis offers several significant advantages over traditional bulk RNA sequencing methods:
High throughput: Enables the analysis of thousands to millions of cells simultaneously.
High sensitivity: Detects rare cell types and subtle gene expression changes.
High accuracy: Uses UMIs to accurately quantify gene expression levels.
Comprehensive data: Provides a detailed view of the transcriptome of each individual cell.
Reproducibility: Utilizes standardized protocols and highly efficient workflows.
Limitations of 10x Single Cell Analysis
Despite its many advantages, 10x single cell analysis has some limitations:
Cost: Can be expensive, especially for large-scale studies.
Data complexity: Generating and analyzing large datasets requires specialized bioinformatics expertise.
Technical challenges: Cell isolation and preparation can be challenging, especially for certain tissues.
Bias: Potential biases in cell capture and RNA extraction can affect the results.
Limited information: Primarily focuses on transcriptomic data, neglecting other important cellular aspects such as proteomics and metabolomics.
Beyond scRNA-seq: 10x Genomics' Expanding Portfolio
10x Genomics has expanded beyond single-cell RNA sequencing, offering technologies like:
10x Visium Spatial Gene Expression: This platform combines spatial information with gene expression data, allowing researchers to map the location of cells and their gene expression profiles within a tissue. This provides valuable context to the scRNA-seq data, revealing spatial organization and interactions between different cell types.
10x Single Cell ATAC-seq: This method profiles the accessibility of chromatin in individual cells, providing insights into gene regulation and epigenetic modifications.
10x Single Cell Multiome ATAC + Gene Expression: This powerful technology combines both ATAC-seq and gene expression data from the same cell, allowing for a more comprehensive understanding of gene regulation and cellular function.
The Future of 10x Single Cell Analysis
The field of 10x single cell analysis is rapidly evolving, with ongoing advancements in technology and data analysis methods. Future developments are likely to include:
Increased throughput: Further improvements in microfluidic technology will enable the analysis of even larger numbers of cells.
Integration of multi-omics data: Combining transcriptomic data with other omics data (proteomics, metabolomics, etc.) will provide a more comprehensive view of cellular function.
Improved data analysis tools: New bioinformatics tools and algorithms will improve the accuracy and efficiency of data analysis.
New applications: 10x single cell analysis will continue to be applied to a wider range of biological questions, driving further discoveries in various fields.
Conclusion
10x single cell analysis has revolutionized biological research by providing unprecedented insights into cellular heterogeneity and gene expression. Its versatility, high throughput, and accuracy have made it a powerful tool for understanding complex biological systems. Despite some limitations, ongoing technological advancements and data analysis improvements are continually expanding its capabilities and applications. The future of this technology is bright, promising even more detailed insights into the intricacies of life at the single-cell level.
FAQs
1. What are the main differences between 10x Genomics and other single-cell RNA sequencing platforms? 10x Genomics excels in high throughput and ease of use, but other platforms may offer advantages in specific applications (e.g., specific cell types or lower costs for smaller experiments).
2. What bioinformatics tools are commonly used for 10x single-cell data analysis? Popular tools include Seurat, Scanpy, and Cell Ranger (provided by 10x Genomics).
3. How can I choose the appropriate 10x Genomics platform for my research question? Consider the type of data needed (RNA, ATAC, etc.), the number of cells, and the spatial resolution required.
4. What are the ethical considerations of using 10x single cell analysis? Data privacy and informed consent are crucial, particularly when working with human samples.
5. What are the common challenges in the data analysis of 10x single cell data? Challenges include data normalization, batch effect correction, and accurate cell type identification.
6. How can I troubleshoot issues during 10x single cell library preparation? Careful attention to cell quality, appropriate reagents, and precise protocol following is key. Contact 10x Genomics technical support for assistance.
7. What are the cost implications of using 10x single cell analysis? Costs vary depending on the scale of the experiment and the specific platform used.
8. How can I validate the results obtained from 10x single cell analysis? Validation involves using independent techniques, such as qPCR, immunohistochemistry, or other single-cell technologies.
9. What are the future trends in 10x single cell analysis? Integration with other omics technologies, improved spatial resolution, and development of more user-friendly analysis tools are expected.
Related Articles:
1. "Deciphering Cellular Heterogeneity using 10x Single Cell RNA Sequencing in Cancer Research": This article focuses on the application of 10x single cell analysis in understanding tumor heterogeneity and identifying cancer stem cells.
2. "A Comprehensive Guide to 10x Visium Spatial Transcriptomics": This article provides a detailed overview of the 10x Visium platform and its applications in mapping gene expression in tissues.
3. "Single Cell Multiome Analysis: Unlocking the Secrets of Cellular Regulation": This article discusses the use of 10x Single Cell Multiome technology to integrate gene expression and chromatin accessibility data.
4. "Best Practices for Data Analysis and Interpretation in 10x Single Cell RNA Sequencing Experiments": This article provides practical guidelines for data processing, normalization, and downstream analysis of 10x single cell data.
5. "Advanced Methods for Cell Type Identification and Trajectory Inference in 10x Single Cell Data": This article explores advanced bioinformatics techniques for identifying cell types and inferring developmental trajectories.
6. "The Role of 10x Single Cell Analysis in Understanding Immune Responses to Viral Infections": This article examines the applications of 10x single cell analysis in the field of immunology.
7. "Comparative Analysis of 10x Genomics and Other Single-Cell RNA Sequencing Platforms": This article compares 10x Genomics with other popular single-cell RNA sequencing platforms.
8. "Troubleshooting Common Issues in 10x Single Cell Library Preparation and Sequencing": This article focuses on troubleshooting common problems encountered in 10x single-cell experiments.
9. "Ethical Considerations in Single-Cell Genomics Research: A Focus on 10x Single Cell Analysis": This article discusses the ethical implications of using 10x single cell analysis, particularly in human research.
| 10x single cell analysis: Tumor Immunology and Immunotherapy - Cellular Methods Part B , 2020-01-28 Tumor Immunology and Immunotherapy - Cellular Methods Part B, Volume 632, the latest release in the Methods in Enzymology series, continues the legacy of this premier serial with quality chapters authored by leaders in the field. Topics covered include Quantitation of calreticulin exposure associated with immunogenic cell death, Side-by-side comparisons of flow cytometry and immunohistochemistry for detection of calreticulin exposure in the course of immunogenic cell death, Quantitative determination of phagocytosis by bone marrow-derived dendritic cells via imaging flow cytometry, Cytofluorometric assessment of dendritic cell-mediated uptake of cancer cell apoptotic bodies, Methods to assess DC-dependent priming of T cell responses by dying cells, and more. |
| 10x single cell analysis: MHC Class-I Loss and Cancer Immune Escape Federico Garrido, 2019-05-28 This book is about the escape strategies used by cancer cells to avoid the immune response of the host. The main characters of this story are the “Antigen Presenting Molecules” and the “T Lymphocytes”. The former are known as the Major Histocompatibility Complex (MHC): the H-2 and the HLA molecules. The latter are a subgroup of white cells travelling all over our body which are capable to distinguish between “self and non self”. Readers will know from the inside about the history of the HLA genetic system and will discover how T lymphocytes recognize and destroy cancer cells. One of the key important questions is: Why tumors arise, develop and metastasize? This book tries to answer this question and will explain how cancer cells become invisible to killer T lymphocytes. The loss of the HLA molecules is a major player in this tumor escape mechanism. Cancer immunotherapy is aimed at stimulating T lymphocytes to destroy tumor cells. However, the clinical response rate is not as high as expected. The molecular mechanisms responsible for MHC/HLA antigen loss play a crucial role in this resistance to immunotherapy. This immune escape mechanism will be discussed in different types of tumors: lung, prostate, bladder and breast...ect. as well as melanoma and lymphoma. This book will be useful to Oncologists, Pathologists and Immunologist that will enter this fascinating area of research. It will be also interesting for biologist, doctoral students and medical residents interested in “Tumor Immunology”. |
| 10x single cell analysis: Single Cell Methods Valentina Proserpio, 2019 This volume provides a comprehensive overview for investigating biology at the level of individual cells. Chapters are organized into eight parts detailing a single-cell lab, single cell DNA-seq, RNA-seq, single cell proteomic and epigenetic, single cell multi-omics, single cell screening, and single cell live imaging. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Single Cell Methods: Sequencing and Proteomics aims to make each experiment easily reproducible in every lab. |
| 10x single cell analysis: Single-cell analysis on the pathophysiology of autoimmune diseases Shiang-Jong Tzeng, InKyeom Kim , Kuang-Hui Sun, 2024-07-11 Despite increasing research to facilitate the understanding of the pathophysiology of autoimmune disorders, the exact cause of the incident of autoimmunity is unknown. Current concepts on the occurrence of autoimmune diseases are thought to involve autoantigens, genetic predisposition, disease triggers, and the breakdown of immune tolerance. In addition to the breakdown of immunological tolerance, one key characteristic of autoimmune disease is that within a single disease there is considerable variability in the clinical manifestation and severity in patients. Single-cell omics have emerged as an effective means of unraveling the complexity and heterogeneity of chronic disease development and therapeutic responses. Recently, advances in cutting-edge spatial profiling of diverse cell types have increased our understanding of how distinct cells interact and orchestrate at specific locations across a tissue landscape in both physiological and pathological contexts at the single-cell level. |
| 10x single cell analysis: Handbook of Statistical Genomics David J. Balding, Ida Moltke, John Marioni, 2019-07-09 A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics. |
| 10x single cell analysis: Clustering Stability Ulrike Von Luxburg, 2010 A popular method for selecting the number of clusters is based on stability arguments: one chooses the number of clusters such that the corresponding clustering results are most stable. In recent years, a series of papers has analyzed the behavior of this method from a theoretical point of view. However, the results are very technical and difficult to interpret for non-experts. In this paper we give a high-level overview about the existing literature on clustering stability. In addition to presenting the results in a slightly informal but accessible way, we relate them to each other and discuss their different implications. |
| 10x single cell analysis: Computational Methods for Single-Cell Data Analysis Guo-Cheng Yuan, 2019-02-14 This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis. |
| 10x single cell analysis: RNA-Seq Analysis: Methods, Applications and Challenges Filippo Geraci, Indrajit Saha, Monica Bianchini, 2020-06-08 |
| 10x single cell analysis: Introduction to Single Cell Omics Xinghua Pan, Shixiu Wu, Sherman M. Weissman, 2019-09-19 Single-cell omics is a progressing frontier that stems from the sequencing of the human genome and the development of omics technologies, particularly genomics, transcriptomics, epigenomics and proteomics, but the sensitivity is now improved to single-cell level. The new generation of methodologies, especially the next generation sequencing (NGS) technology, plays a leading role in genomics related fields; however, the conventional techniques of omics require number of cells to be large, usually on the order of millions of cells, which is hardly accessible in some cases. More importantly, harnessing the power of omics technologies and applying those at the single-cell level are crucial since every cell is specific and unique, and almost every cell population in every systems, derived in either vivo or in vitro, is heterogeneous. Deciphering the heterogeneity of the cell population hence becomes critical for recognizing the mechanism and significance of the system. However, without an extensive examination of individual cells, a massive analysis of cell population would only give an average output of the cells, but neglect the differences among cells. Single-cell omics seeks to study a number of individual cells in parallel for their different dimensions of molecular profile on genome-wide scale, providing unprecedented resolution for the interpretation of both the structure and function of an organ, tissue or other system, as well as the interaction (and communication) and dynamics of single cells or subpopulations of cells and their lineages. Importantly single-cell omics enables the identification of a minor subpopulation of cells that may play a critical role in biological process over a dominant subpolulation such as a cancer and a developing organ. It provides an ultra-sensitive tool for us to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. Besides, it also empowers the clinical investigation of patients when facing a very low quantity of cell available for analysis, such as noninvasive cancer screening with circulating tumor cells (CTC), noninvasive prenatal diagnostics (NIPD) and preimplantation genetic test (PGT) for in vitro fertilization. Single-cell omics greatly promotes the understanding of life at a more fundamental level, bring vast applications in medicine. Accordingly, single-cell omics is also called as single-cell analysis or single-cell biology. Within only a couple of years, single-cell omics, especially transcriptomic sequencing (scRNA-seq), whole genome and exome sequencing (scWGS, scWES), has become robust and broadly accessible. Besides the existing technologies, recently, multiplexing barcode design and combinatorial indexing technology, in combination with microfluidic platform exampled by Drop-seq, or even being independent of microfluidic platform but using a regular PCR-plate, enable us a greater capacity of single cell analysis, switching from one single cell to thousands of single cells in a single test. The unique molecular identifiers (UMIs) allow the amplification bias among the original molecules to be corrected faithfully, resulting in a reliable quantitative measurement of omics in single cells. Of late, a variety of single-cell epigenomics analyses are becoming sophisticated, particularly single cell chromatin accessibility (scATAC-seq) and CpG methylation profiling (scBS-seq, scRRBS-seq). High resolution single molecular Fluorescence in situ hybridization (smFISH) and its revolutionary versions (ex. seqFISH, MERFISH, and so on), in addition to the spatial transcriptome sequencing, make the native relationship of the individual cells of a tissue to be in 3D or 4D format visually and quantitatively clarified. On the other hand, CRISPR/cas9 editing-based In vivo lineage tracing methods enable dynamic profile of a whole developmental process to be accurately displayed. Multi-omics analysis facilitates the study of multi-dimensional regulation and relationship of different elements of the central dogma in a single cell, as well as permitting a clear dissection of the complicated omics heterogeneity of a system. Last but not the least, the technology, biological noise, sequence dropout, and batch effect bring a huge challenge to the bioinformatics of single cell omics. While significant progress in the data analysis has been made since then, revolutionary theory and algorithm logics for single cell omics are expected. Indeed, single-cell analysis exert considerable impacts on the fields of biological studies, particularly cancers, neuron and neural system, stem cells, embryo development and immune system; other than that, it also tremendously motivates pharmaceutic RD, clinical diagnosis and monitoring, as well as precision medicine. This book hereby summarizes the recent developments and general considerations of single-cell analysis, with a detailed presentation on selected technologies and applications. Starting with the experimental design on single-cell omics, the book then emphasizes the consideration on heterogeneity of cancer and other systems. It also gives an introduction of the basic methods and key facts for bioinformatics analysis. Secondary, this book provides a summary of two types of popular technologies, the fundamental tools on single-cell isolation, and the developments of single cell multi-omics, followed by descriptions of FISH technologies, though other popular technologies are not covered here due to the fact that they are intensively described here and there recently. Finally, the book illustrates an elastomer-based integrated fluidic circuit that allows a connection between single cell functional studies combining stimulation, response, imaging and measurement, and corresponding single cell sequencing. This is a model system for single cell functional genomics. In addition, it reports a pipeline for single-cell proteomics with an analysis of the early development of Xenopus embryo, a single-cell qRT-PCR application that defined the subpopulations related to cell cycling, and a new method for synergistic assembly of single cell genome with sequencing of amplification product by phi29 DNA polymerase. Due to the tremendous progresses of single-cell omics in recent years, the topics covered here are incomplete, but each individual topic is excellently addressed, significantly interesting and beneficial to scientists working in or affiliated with this field. |
| 10x single cell analysis: Practical Guide to Life Science Databases Imad Abugessaisa, Takeya Kasukawa, 2022-01-06 This book provides the latest information of life science databases that center in the life science research and drive the development of the field. It introduces the fundamental principles, rationales and methodologies of creating and updating life science databases. The book brings together expertise and renowned researchers in the field of life science databases and brings their experience and tools at the fingertips of the researcher. The book takes bottom-up approach to explain the structure, content and the usability of life science database. Detailed explanation of the content, structure, query and data retrieval are discussed to provide practical use of life science database and to enable the reader to use database and provided tools in practice. The readers will learn the necessary knowledge about the untapped opportunities available in life science databases and how it could be used so as to advance basic research and applied research findings and transforming them to the benefit of human life. Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| 10x single cell analysis: Single Molecule and Single Cell Sequencing Yutaka Suzuki, 2019-04-09 This book presents an overview of the recent technologies in single molecule and single cell sequencing. These sequencing technologies are revolutionizing the way of the genomic studies and the understanding of complex biological systems. The PacBio sequencer has enabled extremely long-read sequencing and the MinION sequencer has made the sequencing possible in developing countries. New developments and technologies are constantly emerging, which will further expand sequencing applications. In parallel, single cell sequencing technologies are rapidly becoming a popular platform. This volume presents not only an updated overview of these technologies, but also of the related developments in bioinformatics. Without powerful bioinformatics software, where rapid progress is taking place, these new technologies will not realize their full potential. All the contributors to this volume have been involved in the development of these technologies and software and have also made significant progress on their applications. This book is intended to be of interest to a wide audience ranging from genome researchers to basic molecular biologists and clinicians. |
| 10x single cell analysis: Handbook of Maize: Its Biology Jeff L. Bennetzen, Sarah C. Hake, 2008-12-25 Handbook of Maize: Its Biology centers on the past, present and future of maize as a model for plant science research and crop improvement. The book includes brief, focused chapters from the foremost maize experts and features a succinct collection of informative images representing the maize germplasm collection. |
| 10x single cell analysis: Transcriptome Analysis Miroslav Blumenberg, 2019-11-20 Transcriptome analysis is the study of the transcriptome, of the complete set of RNA transcripts that are produced under specific circumstances, using high-throughput methods. Transcription profiling, which follows total changes in the behavior of a cell, is used throughout diverse areas of biomedical research, including diagnosis of disease, biomarker discovery, risk assessment of new drugs or environmental chemicals, etc. Transcriptome analysis is most commonly used to compare specific pairs of samples, for example, tumor tissue versus its healthy counterpart. In this volume, Dr. Pyo Hong discusses the role of long RNA sequences in transcriptome analysis, Dr. Shinichi describes the next-generation single-cell sequencing technology developed by his team, Dr. Prasanta presents transcriptome analysis applied to rice under various environmental factors, Dr. Xiangyuan addresses the reproductive systems of flowering plants and Dr. Sadovsky compares codon usage in conifers. |
| 10x single cell analysis: Leukemia Stem Cells César Cobaleda, Isidro Sánchez-García, 2021 |
| 10x single cell analysis: Machine Learning and Mathematical Models for Single-Cell Data Analysis Le Ou-Yang, Xiaofei Zhang, Jiajun Zhang, Jin Chen, Min Wu, 2022-11-29 |
| 10x single cell analysis: Genomics Protocols Michael P. Starkey, Ramnath Elaswarapu, 2008-02-03 We must unashamedly admit that a large part of the motivation for editing Genomics Protocols was selfish. The possibility of assembling in a single volume a unique and comprehensive collection of complete protocols, relevant to our work and the work of our colleagues, was too good an opportunity to miss. We are pleased to report, however, that the outcome is something of use not only to those who are experienced practitioners in the genomics field, but is also valuable to the larger community of researchers who have recognized the potential of genomics research and may themselves be beginning to explore the technologies involved. Some of the techniques described in Genomics Protocols are clearly not restricted to the genomics field; indeed, a prerequisite for many procedures in this discipline is that they require an extremely high throughput, beyond the scope of the average investigator. However, what we have endeavored here to achieve is both to compile a collection of procedures concerned with geno- scale investigations and to incorporate the key components of “bottom-up” and “top-down” approaches to gene finding. The technologies described extend from those traditionally recognized as coming under the genomics umbrella, touch on proteomics (the study of the expressed protein complement of the genome), through to early therapeutic approaches utilizing the potential of genome programs via gene therapy (Chapters 27–30). |
| 10x single cell analysis: The Neuroscience of Creativity Anna Abraham, 2018-10-25 Discover how the creative brain works across musical, literary, visual artistic, kinesthetic and scientific spheres, and how to study it. |
| 10x single cell analysis: The Mouse Nervous System Charles Watson, George Paxinos, Luis Puelles, 2011-11-28 The Mouse Nervous System provides a comprehensive account of the central nervous system of the mouse. The book is aimed at molecular biologists who need a book that introduces them to the anatomy of the mouse brain and spinal cord, but also takes them into the relevant details of development and organization of the area they have chosen to study. The Mouse Nervous System offers a wealth of new information for experienced anatomists who work on mice. The book serves as a valuable resource for researchers and graduate students in neuroscience. Systematic consideration of the anatomy and connections of all regions of the brain and spinal cord by the authors of the most cited rodent brain atlases A major section (12 chapters) on functional systems related to motor control, sensation, and behavioral and emotional states A detailed analysis of gene expression during development of the forebrain by Luis Puelles, the leading researcher in this area Full coverage of the role of gene expression during development and the new field of genetic neuroanatomy using site-specific recombinases Examples of the use of mouse models in the study of neurological illness |
| 10x single cell analysis: Single Cell Analysis Tuhin Subhra Santra, Fan-Gang Tseng, 2021-06-02 Cells are the most fundamental building block of all living organisms. The investigation of any type of disease mechanism and its progression still remains challenging due to cellular heterogeneity characteristics and physiological state of cells in a given population. The bulk measurement of millions of cells together can provide some general information on cells, but it cannot evolve the cellular heterogeneity and molecular dynamics in a certain cell population. Compared to this bulk or the average measurement of a large number of cells together, single-cell analysis can provide detailed information on each cell, which could assist in developing an understanding of the specific biological context of cells, such as tumor progression or issues around stem cells. Single-cell omics can provide valuable information about functional mutation and a copy number of variations of cells. Information from single-cell investigations can help to produce a better understanding of intracellular interactions and environmental responses of cellular organelles, which can be beneficial for therapeutics development and diagnostics purposes. This Special Issue is inviting articles related to single-cell analysis and its advantages, limitations, and future prospects regarding health benefits. |
| 10x single cell analysis: Anthrax in Humans and Animals World Health Organization, 2008 This fourth edition of the anthrax guidelines encompasses a systematic review of the extensive new scientific literature and relevant publications up to end 2007 including all the new information that emerged in the 3-4 years after the anthrax letter events. This updated edition provides information on the disease and its importance, its etiology and ecology, and offers guidance on the detection, diagnostic, epidemiology, disinfection and decontamination, treatment and prophylaxis procedures, as well as control and surveillance processes for anthrax in humans and animals. With two rounds of a rigorous peer-review process, it is a relevant source of information for the management of anthrax in humans and animals. |
| 10x single cell analysis: T-Cell Receptor Signaling Chaohong Liu, 2020-01-14 This volume provides current and new advanced methods and protocols to study T cells. Chapters guide readers through T cell diversity using mass cytometry, analyzing T cells from single cell level, CRISPR/Cas9 techniques to study the T cell activation, techniques to study subsets of Tcell’s, procedures to study artificial antigen presentosomes for T cell activation, techniques to study the T cell development, two-photon microscopy, and MAIT cells. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, T-Cell Receptor Signaling: Methods and Protocols aims to provide a wide range of approaches and be an invaluable resource for present and future generations of T cell researchers. |
| 10x single cell analysis: Cell Line Development Mohamed Al-Rubeai, 2009-08-11 Mammalian cell lines command an effective monopoly for the production of therapeutic proteins that require post-translational modifications. This unique advantage outweighs the costs associated with mammalian cell culture, which are far grater in terms of development time and manufacturing when compared to microbial culture. The development of cell lines has undergone several advances over the years, essentially to meet the requirement to cut the time and costs associated with using such a complex hosts as production platforms. This book provides a comprehensive guide to the methodology involved in the development of cell lines and the cell engineering approach that can be employed to enhance productivity, improve cell function, glycosylation and secretion and control apoptosis. It presents an overall picture of the current topics central to expression engineering including such topics as epigenetics and the use of technologies to overcome positional dependent inactivation, the use of promoter and enhancer sequences for expression of various transgenes, site directed engineering of defined chromosomal sites, and examination of the role of eukaryotic nucleus as the controller of expression of genes that are introduced for production of a desired product. It includes a review of selection methods for high producers and an application developed by a major biopharmaceutical industry to expedite the cell line development process. The potential of cell engineering approch to enhance cell lines through the manipulation of single genes that play important roles in key metabolic and regulatory pathways is also explored throughout. |
| 10x single cell analysis: Interactive Web-Based Data Visualization with R, plotly, and shiny Carson Sievert, 2020-01-30 The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. It is written for the data analyst who wants to leverage the capabilities of interactive web graphics without having to learn web programming. Through many R code examples, you will learn how to tap the extensive functionality of these tools to enhance the presentation and exploration of data. By mastering these concepts and tools, you will impress your colleagues with your ability to quickly generate more informative, engaging, and reproducible interactive graphics using free and open source software that you can share over email, export to pdf, and more. Key Features: Convert static ggplot2 graphics to an interactive web-based form Link, animate, and arrange multiple plots in standalone HTML from R Embed, modify, and respond to plotly graphics in a shiny app Learn best practices for visualizing continuous, discrete, and multivariate data Learn numerous ways to visualize geo-spatial data This book makes heavy use of plotly for graphical rendering, but you will also learn about other R packages that support different phases of a data science workflow, such as tidyr, dplyr, and tidyverse. Along the way, you will gain insight into best practices for visualization of high-dimensional data, statistical graphics, and graphical perception. The printed book is complemented by an interactive website where readers can view movies demonstrating the examples and interact with graphics. |
| 10x single cell analysis: Ovarian Cancer: Molecular & Diagnostic Imaging and Treatment Strategies Heide Schatten, 2021-08-02 The present book on Molecular & Diagnostic Imaging and Treatment Strategies of ovarian cancer is one of two companion books with the second one being focused on Cell and Molecular Biology of Ovarian Cancer. Both books include new exciting aspects of ovarian cancer research with chapters written by experts in their respective fields who contributed their unique expertise in specific ovarian cancer research areas and include cell and molecular details that are important for the specific subtopics. Comprehensive and concise reviews are included of key topics in the field. |
| 10x single cell analysis: Computer and Information Sciences - ISCIS 2005 Pinar Yolum, Tunga Güngör, Fikret Gürgen, Can Özturan, 2005-11-16 This book constitutes the refereed proceedings of the 20th International Symposium on Computer and Information Sciences, ISCIS 2005, held in Istanbul, Turkey in October 2005. The 92 revised full papers presented together with 4 invited talks were carefully reviewed and selected from 491 submissions. The papers are organized in topical sections on computer networks, sensor and satellite networks, security and cryptography, performance evaluation, e-commerce and Web services, multiagent systems, machine learning, information retrieval and natural language processing, image and speech processing, algorithms and database systems, as well as theory of computing. |
| 10x single cell analysis: Statistical Genomics Ewy Mathé, Sean Davis, 2016-03-24 This volume expands on statistical analysis of genomic data by discussing cross-cutting groundwork material, public data repositories, common applications, and representative tools for operating on genomic data. Statistical Genomics: Methods and Protocols is divided into four sections. The first section discusses overview material and resources that can be applied across topics mentioned throughout the book. The second section covers prominent public repositories for genomic data. The third section presents several different biological applications of statistical genomics, and the fourth section highlights software tools that can be used to facilitate ad-hoc analysis and data integration. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible analysis protocols, and tips on troubleshooting and avoiding known pitfalls. Through and practical, Statistical Genomics: Methods and Protocols, explores a range of both applications and tools and is ideal for anyone interested in the statistical analysis of genomic data. |
| 10x single cell analysis: Single-cell Sequencing and Methylation Buwei Yu, Jiaqiang Zhang, Yiming Zeng, Li Li, Xiangdong Wang, 2020-10-14 With the rapid development of biotechnologies, single-cell sequencing has become an important tool for understanding the molecular mechanisms of diseases, defining cellular heterogeneities and characteristics, and identifying intercellular communications and single-cell-based biomarkers. Providing a clear overview of the clinical applications, the book presents state-of-the-art information on immune cell function, cancer progression, infection, and inflammation gained from single-cell DNA or RNA sequencing. Furthermore, it explores the role of target gene methylation in the pathogenesis of diseases, with a focus on respiratory cancer, infection and chronic diseases. As such it is a valuable resource for clinical researchers and physicians, allowing them to refresh their knowledge and improve early diagnosis and therapy for patients. |
| 10x single cell analysis: Practical Web 2.0 Applications with PHP Quentin Zervaas, 2008-03-11 In Practical PHP Web 2.0 Applications, PHP, MySQL, CSS, XHTML, and JavaScript/Ajax development techniques are brought together to show you how to create the hottest PHP web applications, from planning and design up to final implementation, without going over unnecessary basics that will hold you back. This book includes must-have application features such as search functionality, maps, blogs, dynamic image galleries, and personalized user areas. It covers everything in a practical, tutorial style so you can start working on your own projects as quickly as possible. |
| 10x single cell analysis: Relative Distribution Methods in the Social Sciences Mark S. Handcock, Martina Morris, 2006-05-10 This monograph presents methods for full comparative distributional analysis based on the relative distribution. This provides a general integrated framework for analysis, a graphical component that simplifies exploratory data analysis and display, a statistically valid basis for the development of hypothesis-driven summary measures, and the potential for decomposition - enabling the examination of complex hypotheses regarding the origins of distributional changes within and between groups. Written for data analysts and those interested in measurement, the text can also serve as a textbook for a course on distributional methods. |
| 10x single cell analysis: Intestinal Stem Cells Paloma Ordóñez-Morán, 2021-08-07 This detailed book encapsulates the most up-to-date methods of the intestinal stem cell field and provides guidance on a variety of techniques for studying intestinal stem cells properties. Beginning with a section on in vitro techniques to study different aspects of the intestinal stem cell functions by innovative imaging and functional assays, the volume continues with chapters detailing the single-cell transcriptional profiling method, the isolation of intestinal crypts to generate and establish 3D organoids, as well as different animal models of gastrointestinal cancer and examples of the use of in vivo methods for studying intestinal tumor-initiating cells or cancer stem cells. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and state-of-the-art, Intestinal Stem Cells: Methods and Protocols aims to provide comprehensive and easy to follow protocols designed to be helpful to both seasoned researchers and newcomers to this dynamic field. |
| 10x single cell analysis: Single Cell Transcriptomics Raffaele A. Calogero, Vladimir Benes, 2022-12-10 This volume provides up-to-date methods on single cell wet and bioinformatics protocols based on the researcher experiment requirements. Chapters detail basic analytical procedures, single-cell data QC, dimensionality reduction, clustering, cluster-specific features selection, RNA velocity, multi-modal data integration, and single cell RNA editing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and comprehensive, Single Cell Transcriptomics: Methods and Protocols aims to be a valuable resource for all researchers interested in learning more about this important and developing field. |
| 10x single cell analysis: Single-cell Analysis on Microfluidic Platforms Samuel Kim, 2009 |
| 10x single cell analysis: The Biology of Mammalian Spermatogonia Jon M. Oatley, Michael D. Griswold, 2017-11-20 This book provides a resource of current understandings about various aspects of the biology of spermatogonia in mammals. Considering that covering the entire gamut of all things spermatogonia is a difficult task, specific topics were selected to provide foundational information that will be useful for seasoned researchers in the field of germ cell biology as well as investigators entering the area. Looking to the future, the editors predict that the foundational information provided in this book -- combined with the advent of new tools and budding interests in use of non-rodent mammalian models -- will produce another major advance in knowledge regarding the biology of spermatogonia over the next decade. In particular, we anticipate that the core molecular machinery driving different spermatogonial states in most, if not all, mammals will be described fully, the extrinsic signals emanating from somatic support cell populations to influence spermatogonial functions will become fully known, and the capacity to derive long-term cultures of SSCs and transplant the population to regenerate spermatogenesis and fertility will become a reality for higher order mammals. |
| 10x single cell analysis: Transcriptome Profiling Mohammad Ajmal Ali, Joongku Lee, 2022-10-07 Transcriptome Profiling: Progress and Prospects assists readers in assessing and interpreting a large number of genes, up to and including an entire genome. It provides key insights into the latest tools and techniques used in transcriptomics and its relevant topics which can reveal a global snapshot of the complete RNA component of a cell at a given time. This snapshot, in turn, enables the distinction between different cell types, different disease states, and different time points during development. Transcriptome analysis has been a key area of biological inquiry for decades. The next-generation sequencing technologies have revolutionized transcriptomics by providing opportunities for multidimensional examinations of cellular transcriptomes in which high-throughput expression data are obtained at a single-base resolution. Transcriptome analysis has evolved from the detection of single RNA molecules to large-scale gene expression profiling and genome annotation initiatives. Written by a team of global experts, key topics in Transcriptome Profiling include transcriptome characterization, expression analysis of transcripts, transcriptome and gene regulation, transcriptome profiling and human health, medicinal plants transcriptomics, transcriptomics and genetic engineering, transcriptomics in agriculture, and phylotranscriptomics. - Presents recent development in the tools and techniques in transcriptomic characterization - Integrates expression analysis of transcripts and gene regulation - Includes the application of transcriptomics in human health, genetic engineering and agriculture |
| 10x single cell analysis: Biology for AP ® Courses Julianne Zedalis, John Eggebrecht, 2017-10-16 Biology for AP® courses covers the scope and sequence requirements of a typical two-semester Advanced Placement® biology course. The text provides comprehensive coverage of foundational research and core biology concepts through an evolutionary lens. Biology for AP® Courses was designed to meet and exceed the requirements of the College Board’s AP® Biology framework while allowing significant flexibility for instructors. Each section of the book includes an introduction based on the AP® curriculum and includes rich features that engage students in scientific practice and AP® test preparation; it also highlights careers and research opportunities in biological sciences. |
| 10x single cell analysis: Single-Cell OMICs Analyses in Cardiovascular Diseases , 2024-05-14 Single-cell OMICs analyses have recently become one of the most promising tools to probe biology at the cellular level, in large part due to its ability to address issues beyond the bulk analysis – a window into cellular heterogeneity. The ability to profile transcriptomic, epigenomic, proteomics, and metabolomics at the single cell level including more recently the spatial information has enhanced our ability to understand interactions between biomolecules in different contexts leading to the discovery of specific cellular subpopulations as well as biological mechanisms underlying pathologies which may be amenable to therapeutic interventions. The scale and availability of a variety of technologies to measure intricate molecular details have provided an impetus to research in many disease areas, including cardiovascular medicine. |
| 10x single cell analysis: Cereal Genomics Robert J. Henry, Agnelo Furtado, 2013-11-16 In Cereal Genomics: Methods and Protocols, expert researchers provides modern protocols for the analysis and manipulation of cereal genomes. Techniques for isolation and analysis of DNA and RNA from both the vegetative tissues and from the more challenging seeds of cereals are described. Tools for the isolation, characterization and functional analysis of cereal genes and their transcripts are detailed. Methods for molecular screening of cereals and for their genetic transformation are also covered. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Cereal Genomics: Methods and Protocols provides a comprehensive resource for those studying cereal genomes. |
| 10x single cell analysis: RNA Amplification and Analysis Mekbib Astatke, |
| 10x single cell analysis: RNA Modification in Human Cancers: Roles and Therapeutic Implications You Zhou, Tao Huang, Tianbao Li, Jing Sun, 2022-04-26 |
| 10x single cell analysis: Stem Cells in Oral Cavity: From Development to Regeneration Mikihito Kajiya, Anne George, Takehito Ouchi, Giovanna Orsini, 2022-02-22 |
Cell Preparation for Single Cell Protocols - 10x Genomics
10x Genomics Single Cell protocols require a suspension of viable single cells or nuclei as input. Minimizing the presence of cellular aggregates, dead cells, noncellular nucleic acids, and …
Lexogen 10X Single Cell Sample Preparation Guide
Samples for 10X single-cell RNA sequencing should be collected and prepared carefully to maximize cell viability and nuclear integrity. Recommendations for sample preparation are …
Novogene 10x Single Cell Services
By utilizing this technique, a comprehensive analysis of stem cell heterogeneity is conducted. The analysis includes identifying diverse phenotypes, pinpointing specific markers for various stem …
Getting Started with Single Cell Gene Expression
signed for quick, interactive single cell data visualization and analysis. Built to accelerate the discovery of new marker genes, you can identify rare cell types and explore novel substructures …
Technical overview – Kinnex library preparation using Kinnex …
Enzymatic workflow steps for construction of 16-segment Kinnex arrays from 10x single cell cDNA. Enzymatic workflow steps for DNA damage repair & nuclease treatment of Kinnex single-cell …
Explore the transcriptome with single-cell resolution - Illumina
Loupe Browser software (10x Genomics) makes it easy to visualize and explore single‐cell gene expression data and characterize the heterogeneity of the sample.
Neutrophil Analysis in 10x Genomics Single Cell Gene …
The Capturing Neutrophils in 10x Single Cell Gene Expression Data Tutorial provides step by step instructions for performing some of the analysis steps described in this Technical Note using Cell …
Single-cell analysis: best practices and unsolved problems
Jun 9, 2022 · Let's walksprint through a typical*scRNA-seq analysis. Luecken, M. D. & Theis, F. J. Current best practices in single-cell RNA-seq analysis: a tutorial. Mol. Syst. Biol.15, (2019). Credit …
Analysing 10X Single Cell RNA-Seq Data - Babraham Institute
•How 10X single cell RNA-Seq works •Evaluating CellRanger QC –[Exercise] Looking at CellRanger QC reports •Dimensionality Reduction (PCA and tSNE) –[Exercise] Using the Loupe cell browser …
Introduction to Single Cell RNA-Seq Data Analysis
Single Cell RNA-Seq Applications •Explore which cell types are present in a tissue •Identify unknown/rare cell types or states •Elucidate the changes in gene expression during …
Application note - MAS-Seq for single-cell isoform sequencing
The MAS-Seq for 10x Single Cell 3’ kit offers an end-to- end solution for single-cell RNA isoform sequencing from sample preparation to bioinformatics analysis.
Novogene 10x Single Cell Services
By utilizing this technique, a comprehensive analysis of stem cell heterogeneity is conducted. The analysis includes identifying diverse phenotypes, pinpointing specific markers for various stem …
Flow Cytometry Guidance for Single Cell Protocols - 10x …
10x Genomics Single Cell assays require a suspension of high-quality single cells or nuclei as input. Cell sorting using flow cytometry enables the enrichment of specific cell types as well as removal …
RNA-seq (Single Cell) data analysis - Emory University
Jan 23, 2019 · This document aims to provide a workflow for analysis of 10x Genomics@ ChromiumTM scRNA-seq data. 10x Genomics protocols are droplet-based; supports the …
Chromium Single Cell 5' Barcode Enabled Antigen Mapping …
Chromium Single Cell 5’ Barcode Enabled Antigen Mapping (BEAM) enables multiplexed screening of antigen targets to match unique antigens with their corresponding B-cell receptors (BCRs) and …
Introduction of Novogene 10x Single-cell Service
The 10x Genomics single-cell platform quickly distributes single cells into the GEMs microfluidic system through the micro-fluidic system. It is done by partitioning thousands of cells into …
Single Cell Protocols - 10x Genomics
10x Genomics® Single Cell Protocols require a suspension of viable single cells as input. Minimizing the presence of cellular aggregates, dead cells, non-cellular nucleic acids and potential inhibitors …
Application of 10x Single-cell Gene Expression in Oncology …
Validate the effectiveness of target drugs through single-cell transcriptome analysis. Investigate differences in drug resistance at the individual cell level. Provide valuable insights for the …
Kinnex single-cell RNA kit for single- cell isoform sequencing
The Kinnex single-cell RNA kit offers an end-to-end solution for single-cell RNA isoform sequencing from sample preparation to bioinformatics analysis. • Supports cDNA from 10x Chromium Next …
Getting Started: Single Cell ATAC - 10x Genomics
Consult the user guide for a consumables and equipment list validated by 10x Genomics for executing the Chromium Single Cell ATAC protocol. To enable seamless experimental planning, a …
Cell Preparation for Single Cell Protocols - 10x Genom…
10x Genomics Single Cell protocols require a suspension of viable single cells or nuclei as input. Minimizing …
Lexogen 10X Single Cell Sample Preparation Guide
Samples for 10X single-cell RNA sequencing should be collected and prepared carefully to maximize cell …
Novogene 10x Single Cell Services
By utilizing this technique, a comprehensive analysis of stem cell heterogeneity is conducted. The …
Getting Started with Single Cell Gene Expression
signed for quick, interactive single cell data visualization and analysis. Built to accelerate the discovery of new …
Technical overview – Kinnex library preparation using Ki…
Enzymatic workflow steps for construction of 16-segment Kinnex arrays from 10x single cell cDNA. …
