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Computational Methods for Single-Cell Data Analysis

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Cover of 'Computational Methods for Single-Cell Data Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Archean Rare-Metal Pegmatites
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    Chapter 1 Quality Control of Single-Cell RNA-seq
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    Chapter 2 Normalization for Single-Cell RNA-Seq Data Analysis
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    Chapter 3 Analysis of Technical and Biological Variability in Single-Cell RNA Sequencing
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    Chapter 3 Petrography and Mineralogy
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    Chapter 4 Smart Tourism Destination in Smart Cities Paradigm: A Model for Antalya
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    Chapter 4 Geochemistry of LCT Pegmatites
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    Chapter 4 Identification of Cell Types from Single-Cell Transcriptomic Data
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    Chapter 5 Rare Cell Type Detection
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    Chapter 5 Geochronology of Archean LCT Pegmatites
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    Chapter 6 Radiogenic and Stable Isotopes, Fluid Inclusions
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    Chapter 6 scMCA: A Tool to Define Mouse Cell Types Based on Single-Cell Digital Expression
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    Chapter 7 Differential Pathway Analysis
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    Chapter 7 Genesis of Massive Pollucite Mineralisation in Archean LCT Pegmatites
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    Chapter 8 Pseudotime Reconstruction Using TSCAN
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    Chapter 9 Estimating Differentiation Potency of Single Cells Using Single-Cell Entropy (SCENT)
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    Chapter 10 Inference of Gene Co-expression Networks from Single-Cell RNA-Sequencing Data
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    Chapter 11 Single-Cell Allele-Specific Gene Expression Analysis
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    Chapter 12 Using BRIE to Detect and Analyze Splicing Isoforms in scRNA-Seq Data
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    Chapter 13 Preprocessing and Computational Analysis of Single-Cell Epigenomic Datasets
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    Chapter 14 Experimental and Computational Approaches for Single-Cell Enhancer Perturbation Assay
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    Chapter 15 Antigen Receptor Sequence Reconstruction and Clonality Inference from scRNA-Seq Data
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    Chapter 16 A Hidden Markov Random Field Model for Detecting Domain Organizations from Spatial Transcriptomic Data
Attention for Chapter 10: Inference of Gene Co-expression Networks from Single-Cell RNA-Sequencing Data
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