Table of 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.