Background: KRAS is mutated in 90% of pancreatic cancers making it a seemingly ideal target for treatment and yet, with the exception of the rare G12C mutation, KRAS is undruggable for the vast majority of pancreatic patients. Herein, we characterize, in silico, KRAS methylation-derived mutation clonal and subclonal diversity in PDAC and examine their impact upon clinical outcomes. Methods: We developed a mutation methylation (MM) clonality workflow for gene mutation assignment as clonal versus subclonal and applied it genome-wide to TCGA data. For comparison, we used the cancer cell fraction (CCF) clonality prediction. We examined clinical outcomes by comparing in months (mos), Kaplan-Meier estimated overall survival (OS) using a log-rank test and a cox model for testing several features. We performed differential gene expression, differential gene correlation, and gene set enrichment analyses (GSEA) between KRAS MM clonal versus subclonal early stage pancreatic patients. Results: Using 104 TCGA early stage pancreatic cancer patient tumors from TCGA with mutation, methylation and clinical outcomes data, we defined KRAS MM clonality (n = 70 clonal, n = 34 subclonal) and CCF clonality (n = 74 clonal, n = 28 subclonal) tumors. Clonality assignment between methods was 53% clonal and 17% subclonal concordant, and 19% discordant among samples. KRAS MM clonality was associated with significantly (p = 0.046) shorter OS (median OS = 11.5 mos) as compared to the KRAS subclonal group (median OS = 15 mos). By comparison, KRAS CCF clonal and subclonal patient groups did not differ in their OS. When RNA-Seq derived subtypes for pancreatic cancer were included in a model with our KRAS MM clonality marker, only our marker remained as significantly associated with OS. Median KRAS gene expression was significantly (p = 0.01) higher in the KRAS MM clonal versus subclonal group. A GSEA showed enrichment of MYC targets in the KRAS clonal group. We identified 72, mostly protein coding genes residing on chromosomes 5q, 7p and 8p that correlated with KRAS gene expression only in the subclonal group. Conclusions: Our analyses shows a potential clonality dissection of the established 90% KRAS mutation rate in pancreatic cancer, which based on our MM workflow, may be dissected into 61% KRAS clonal and 30% KRAS subclonal. By assigning clonality based on another DNA data type using CCF, we obtain 65% KRAS clonal and 25% KRAS subclonal. Thus, regardless of which DNA-based workflow, overall, the KRAS clonality rates are similar. There is a notable difference however in patient-level assignment of KRAS clonality as only our workflow showed poor OS associated with KRAS clonality. The introduction of a methylation-based mutation clonality marker could prove invaluable when used in combination with methylation-based circulating tumor DNA assays for patient and treatment selection, and clinical trial monitoring of tumor responses.