Aim: Assessing deglutitive esophagogastric junction (EGJ) relaxation is an essential focus of clinical manometry. Our aim was to apply automated algorithmic analyses to high resolution manometry (HRM) studies to ascertain the optimal method for discriminating normal from abnormal deglutitive EGJ relaxation. Methods: All 473 subjects (73 controls) were studied with a 36-channel solid-state HRM assembly during water swallows. Patient were classify as: 1) achalasia, 2) post-fundoplication, 3) non-achalasia with normal deglutitive EGJ relaxation, or 4) functional obstruction (preserved peristalsis with incomplete EGJ relaxation). Automated computer programs assessed the adequacy of EGJ relaxation using progressively complex analysis routines to compensate for esophageal shortening, crural diaphragm contraction and catheter movement, all potential confounders. Results: The single sensor method of assessing EGJ relaxation had a sensitivity of only 52% for detecting achalasia. Of the automated HRM analysis paradigms tested, the 4s integrated relaxation pressure (IRP) using a cutoff of 15 mmHg performed optimally with 98% sensitivity and 96% specificity in the detection of achalasia. We also identified a heterogeneous group of 26 patients with functional EGJ obstruction attributed to variant achalasia and other diverse pathology. Conclusion: Although, further clinical experience will ultimately judge, it is our expectation that applying rigorous methodology such as described herein to the analysis of HRM studies will improve the consistency in the interpretation of clinical manometry and prove useful in guiding clinical management.