To assess the dosimetric consequence of inter-fractional setup shifts on helical tomotherapy plans with self-developed independent dose calculation software MU-Tomo. A 2nd dose validation software for helical TomoTherapy , called MU-Tomo, has been developed to independently validates point dose upon archived patient documents, initial coordinates and planned dose of the point of calculation, and common dosimetric functions. This work has studied a hundred helical tomotherapy patients from five different treatment sites (30 prostate, 26 head and neck, 18 lung, 17 pelvis, and 9 brain patients). The daily setup shifts were quantified and grouped into systematic (mean daily setup shift for each patient) and random shifts (shifts after corresponding systematic shifts subtraction). Both Systematic and random shifts were incorporated into MU-Tomo to evaluate the systematic and random variations of dosimetric consequences, separately. Systematic variations showed dose deviation with the largest one -10.02% compared to the planned dose and overall SD 3%. Mean random variations showed dose deviation with the largest one -5.65% compared to the planned dose and overall SD 1.9%. According to the ANOVA analyses, random dosimetric variations were found significantly different among specific patient, while systematic dosimetric variations were significantly different between head and neck and brain group and body group. No significant differences were discovered among specific patients for systematic variations, and no significant differences were observed within each of the two groups for random variations. Dosimetric consequences are not significantly correlated with treatment fraction number according to the Pearson correlation analysis. By comparing doses without any shift and with the random shift, the overall dosimetric impacts to each patient are small with the mean value -0.0053% and SD of 1.11%, and 99% of the averaged variation results were within 3.5%. For helical tomotherapy modality, the overall dosimetric impact from random variations is small; instead, systematic shifts cause more dosimetric impact.