Statistical Genomics

Chapter 1 Multi-omics Data Deconvolution and Integration: New Methods, Insights, and Translational Implications

Chapter 2 Statistical and Machine Learning Methods for Discovering Prognostic Biomarkers for Survival Outcomes

Chapter 4 Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper

Chapter 5 Statistical Methods for Integrative Clustering of Multi-omics Data

Chapter 6 Analysis of Single-Cell RNA-seq Data

Chapter 7 A Primer on Preprocessing, Visualization, Clustering, and Phenotyping of Barcode-Based Spatial Transcriptomics Data

Chapter 8 Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data

Chapter 9 Statistical Analysis in ChIP-seq-Related Applications

Chapter 10 Bioinformatic and Statistical Analysis of Microbiome Data

Chapter 11 Statistical and Computational Methods for Microbial Strain Analysis

Chapter 12 Statistics and Machine Learning in Mass Spectrometry-Based Metabolomics Analysis

Chapter 13 Statistical and Computational Methods for Proteogenomic Data Analysis

Chapter 14 Pharmacogenomic and Statistical Analysis

Chapter 15 Statistical Methods for Disease Risk Prediction with Genotype Data

Chapter 16 Statistical Methods Inspired by Challenges in Pediatric Cancer Multi-omics