Variant annotation is a fundamental objective in mammalian functional genomics. Deep mutational scanning (DMS) is a well-established method for annotating human gene variants, while CRISPR base editing has recently emerged as a high-throughput alternative. However, questions persist regarding the ability of base editing to annotate variant function at scale and the extent of downstream experimental validation required. This dissertation presents the first direct comparison of DMS and adenosine base editing in the same lab and cell line. We demonstrate that while single-edit guides provide high reliability, direct sequencing of genomic edits achieves superior correlation when multiple edits are unavoidable. Building on these findings, we applied base editing to investigate the drug resistance profile of asciminib, a first-in-class allosteric BCR-ABL inhibitor. The base editing screen revealed resistance hotspots across the ABL SH3, SH2, linker, and kinase domains. To address the inherent limitations of base editing, such as editing diversity and coverage, DMS was employed to validate these hotspots, confirming the presence of known and novel potent resistance mutations. A key strength of base editing is the reusability of guide libraries across genetic backgrounds, enabling broader insights. For example, the common resistance mutation Y253H, associated with earlier-generation ABL inhibitors like imatinib and nilotinib, was found to retain sensitivity to asciminib. To explore potential epistatic interactions with secondary mutations, a base editor screen was performed in K562 cells harboring the Y253H mutation. The results revealed that while Y253H and V73A individually remain sensitive to asciminib, their combination confers resistance by preventing asciminib-induced autoinhibition. This work demonstrates the versatility and complementarity of base editing and DMS for functional variant annotation and drug resistance studies. By leveraging the unique strengths of each approach, this research establishes a framework for elucidating resistance mechanisms and advancing precision medicine in cancer therapeutics.