Learn how to merge and integrate single-cell RNA sequencing datasets to correct for batch effects using the Seurat package in R. Follow a detailed workflow that covers study design, data integration types, batch correction methods, and step-by-step instructions for downloading, reading, merging, and analyzing scRNA-seq data. Explore quality control, filtering, and visualization techniques to identify and address batch effects. Compare UMAPs before and after integration to assess the effectiveness of the process. Gain practical insights into handling large-scale single-cell genomics data and applying advanced bioinformatics techniques for improved analysis and interpretation of complex biological datasets.