DNA methylation plays a crucial role in regulating gene expression and is a hallmark of epigenetic dysregulation in human tumors. High-throughput DNA methylation profiling can unravel intricate patterns in cancer. Moreover, understanding immune cell dynamics is essential for comprehending cancer progression and treatment response. Using DNA methylation data in immune cells, we can apply deconvolution algorithms estimate proportions of major immune cell types, providing insights into immune status and its implications in cancer. Functional analysis can identify specific overrepresented or underrepresented immune cell subsets, potentially uncovering novel biomarkers or therapeutic targets. This pipeline presents a detailed workflow in RStudio for DNA methylation studies and immune cell deconvolution, enhancing reproducibility and efficiency. The workflow integrates preprocessing, analysis, and visualization steps, facilitating robust inference of cell-type proportions from DNA methylation data.