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Computational methods for single-cell data analysis / edited by Guo-Cheng Yuan.
Format
Book
Language
English
Published/Created
New York : Humana Press ; Springer, [2019]
Description
x, 271 pages : illustrations ; 26 cm.
Availability
Available Online
Springer Nature - Complete Protocols
Copies in the Library
Location
Call Number
Status
Location Service
Notes
ReCAP - Remote Storage
QH506 .M45 1984 vol.1935
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Details
Subject(s)
Cytology
—
Research
—
Laboratory manuals
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Editor
Yuan, Guo-Cheng
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Library of Congress genre(s)
Laboratory manuals
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Series
Methods in molecular biology (Clifton, N.J.) ; v. 1935.
[More in this series]
Springer protocols (Series)
[More in this series]
Springer Protocols
Methods in molecular biology, 1064-3745 ; 1935
Bibliographic references
Includes bibliographical references and index.
Contents
Quality control of single-cell RNA-seq / Peng Jiang
Normalization for single-cell RNA-seq data analysis / Rhonda Bacher
Analysis of technical and biological variability in single-cell RNA sequencing / Beomseok Kim, Eunmin Lee, and Jong Kyoung Kim
Identification of cell types from single-cell transcriptomic data / Karthik Shekhar and Vilas Menon
Rare cell type detection / Lan Jiang
scMCA : a tool to define mouse cell types based on single-cell digital expression / Huiyu Sun, Yincong Zhou, Lijiang Fei, Haide Chen, and Guoji Guo
Differential pathway analysis / Jean Fan
Pseudotime reconstruction using TSCAN / Zhicheng Ji and Hongkai Ji
Estimating differentiation potency of single cells using single-cell entropy (SCENT) / Weiyan Chen and Andrew E. Teschendorff
Inference of gene co-expression networks from single-cell RNA-sequencing data / Alicia T. Lamere and Jun Li
Single-cell allele-specific gene expression analysis / Meichen Dong and Yuchao Jiang
Using BRIE to detect and analyze splicing isoforms in scRNA-Seq data / Yuanhua Huang and Guido Sanguinetti
Preprocessing and computational analysis of single-cell epigenomic datasets / Caleb Lareau, Divy Kangeyan, and Martin J. Aryee
Experimental and computational approaches for single-cell enhancer perturbation assay / Shiqi Xie and Gary C. Hon
Antigen receptor sequence reconstruction and clonality inference from scRNA-Seq data / Ida Lindeman and Michael J. T. Stubbington
Hidden markov random field model for detecting domain organizations from spatial transcriptomic data / Qian Zhu.
Show 13 more Contents items
ISBN
9781493990566 (hardcover)
149399056X (hardcover)
LCCN
2018967307
OCLC
1057652965
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Computational Methods for Single-Cell Data Analysis [electronic resource] / edited by Guo-Cheng Yuan.
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99125158067606421