Overview

This volume provides a collection of protocols from researchers in the statistical genomics field. Chapters focus on integrating genomics with other “omics” data, such as transcriptomics, epigenomics, proteomics, metabolomics, and metagenomics. 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 thorough, Statistical Genomics hopes that by covering these diverse and timely topics researchers are provided insights into future directions and priorities of pan-omics and the precision medicine era.

Full Product Details

Author:   Brooke Fridley ,  Xuefeng Wang
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   1st ed. 2023
Volume:   2629
Weight:   0.932kg
ISBN:  

9781071629857

ISBN 10:   1071629859
Pages:   377
Publication Date:   17 March 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Multi-omics data deconvolution and integration: new methods, insights and translational implications Xuefeng Wang and Brooke L Fridley   2. Multi-omics data deconvolution and integration: new methods, insights and translational implications Xuefeng Wang and Brooke L Fridley   3. Cell-type deconvolution of bulk DNA methylation data with EpiSCORE Tianyu Zhu and Andrew E. Teschendorff 4. Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper Chloé B. Steen, Bogdan A. Luca, Ash A. Alizadeh, Andrew J. Gentles, and Aaron M. Newman   5. Statistical methods for integrative clustering of multi-omics data Prabhakar Chalise, Deukwoo Kwon, Brooke L. Fridley, and Qianxing Mo   6. Analysis of Single-Cell RNA-seq Data Xiaoru Dong   7. A Primer On Pre-Processing, Visualization, Clustering, and Phenotyping of Barcode-Based Spatial Transcriptomics Data Oscar Ospina, Alex Soupir, and Brooke L. Fridley   8. Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data Julia Wrobel, Coleman Harris, and Simon Vandekar   9. Statistical Analysis in ChIP-seq Related Applications Mingxiang Teng   10. Bioinformatics and Statistical Analysis of Microbiome Data Youngchul Kim   11. Statistical and Computational Methods for Microbial Strain Analysis Siyuan Ma and Hongzhe Li   12. Statistics and machine learning in mass spectrometry-based metabolomics analysis Sili Fan, Christopher M. Wilson, Brooke L. Fridley, and Qian Li   13. Statistical and Computational Methods for Proteogenomic Data Analysis Xiaoyu Song   14. Pharmacogenomics and Statistical Analysis Haimeng Bai, Xueyi Zhang, and William S. Bush   15. Statistical methods for disease risk prediction with genotype data Xiaoxuan Xia, Yexian Zhang, Yingying Wei, and Maggie Haitian Wang   16. Statistical Methods Inspired by Challenges in Pediatric Cancer Multi-Omics Xueyuan Cao, Abdelraham H. Elsayed, and Stanley B. Pounds

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