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Experimental and Computational Tools for Single Cell Analysis in Cancer Diagnostics

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Release : 2020
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Kind : eBook
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Book Synopsis Experimental and Computational Tools for Single Cell Analysis in Cancer Diagnostics by : Manibarathi Vaithiyanathan

Download or read book Experimental and Computational Tools for Single Cell Analysis in Cancer Diagnostics written by Manibarathi Vaithiyanathan. This book was released on 2020. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Methods for Single-Cell Data Analysis

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Release : 2019-02-14
Genre : Science
Kind : eBook
Book Rating : 566/5 ( reviews)

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Book Synopsis Computational Methods for Single-Cell Data Analysis by : Guo-Cheng Yuan

Download or read book Computational Methods for Single-Cell Data Analysis written by Guo-Cheng Yuan. This book was released on 2019-02-14. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Single Cell Omics

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Release : 2019-09-19
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Kind : eBook
Book Rating : 209/5 ( reviews)

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Book Synopsis Introduction to Single Cell Omics by : Xinghua Pan

Download or read book Introduction to Single Cell Omics written by Xinghua Pan. This book was released on 2019-09-19. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Revealing Translational and Fundamental Insights Via Computational Analysis of Single-cell Sequencing Data

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Release : 2023
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Book Synopsis Revealing Translational and Fundamental Insights Via Computational Analysis of Single-cell Sequencing Data by : Jessica Lu Zhou

Download or read book Revealing Translational and Fundamental Insights Via Computational Analysis of Single-cell Sequencing Data written by Jessica Lu Zhou. This book was released on 2023. Available in PDF, EPUB and Kindle. Book excerpt: Single-cell sequencing has emerged as a powerful tool for dissecting cellular heterogeneity and providing cell type-specific biological insights. Single-cell sequencing technologies have rapidly proliferated over the last decade, leading to an explosion of data generated from such experiments. However, several challenges exist in the computational analysis of single-cell sequencing data due to its large and complex nature, including the need for sophisticated statistical methods to distinguish biologically meaningful signals from noise, the integration of single-cell sequencing data with other types of biological information, and the development of scalable and reproducible computational pipelines that can handle the large and complex nature of the data. In this dissertation, I present two distinct projects analyzing single-cell sequencing data. The first is of an analytical nature and tackles a translational question. In this project, I built computational pipelines for processing and analyzing single-nucleus RNA- and ATAC-sequencing datasets generated from the amygdalae of genetically diverse heterogenous stock rats, which were subjected to a behavioral protocol for studying addiction-like behaviors following cocaine self-administration. In doing so, I provide a standard reference for analyzing such data as well as reveal cell type-specific insights into the molecular underpinnings of cocaine addiction. The second project is oriented towards methods development and seeks to understand the fundamental biological question of transcriptional regulation. Here, I developed a statistical framework for simulating and modeling data from single-cell CRISPR regulatory screens and used it to perform a genome-wide interrogation of epistatic-like interactions between enhancer pairs. I found that multiple enhancers act together in a multiplicative fashion with little evidence for interactive effects between them. This work revealed novel insights into the collective behavior of multiple regulatory elements and provides a tool that can be applied to future datasets generated from such experiments. This dissertation exemplifies how computational methods can be applied in different contexts to extract meaning from a variety of single-cell sequencing modalities. By tackling both a translational and fundamental biological question, I have showcased the breadth of what can be revealed by studying single-cell sequencing data and the computational methods necessary to extract this information.

Computational Methods for Single-cell Data Analysis

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Author :
Release : 2019
Genre : Cytology
Kind : eBook
Book Rating : 573/5 ( reviews)

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Book Synopsis Computational Methods for Single-cell Data Analysis by : Guo-Cheng Yuan

Download or read book Computational Methods for Single-cell Data Analysis written by Guo-Cheng Yuan. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt:

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