Statistical Genomics / edited by Brooke Fridley, Xuefeng Wang.

Format:

Book

Contributor:

Fridley, Brooke., Editor.

Wang, Xuefeng., Editor.

Series:

Methods in Molecular Biology, 1940-6029 ; 2629

Language:

English

Subjects (All):

Genomics.

Local Subjects:

Genomics.

Physical Description:

1 online resource (XI, 377 p. 79 illus., 72 illus. in color.)

Edition:

1st ed. 2023.

Place of Publication:

New York, NY : Springer US : Imprint: Humana, 2023.

Summary:

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.

Contents:

Multi-omics data deconvolution and integration: new methods, insights and translational implications

Multi-omics data deconvolution and integration: new methods, insights and translational implications

Cell-type deconvolution of bulk DNA methylation data with EpiSCORE

Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper

Statistical methods for integrative clustering of multi-omics data

Analysis of Single-Cell RNA-seq Data

A Primer On Pre-Processing, Visualization, Clustering, and Phenotyping of Barcode-Based Spatial Transcriptomics Data

Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data

Statistical Analysis in ChIP-seq Related Applications

Bioinformatics and Statistical Analysis of Microbiome Data

Statistical and Computational Methods for Microbial Strain Analysis

Statistics and machine learning in mass spectrometry-based metabolomics analysis

Statistical and Computational Methods for Proteogenomic Data Analysis

Pharmacogenomics and Statistical Analysis

Statistical methods for disease risk prediction with genotype data

Statistical Methods Inspired by Challenges in Pediatric Cancer Multi-Omics.

ISBN:

9781071629864

1071629867