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Hemoglobin (Hb) is the oxygen-carrying protein in mammals and is probably the most studied protein in history. One ongoing area of Hb research is the mechanism of Hb transport and release of nitric oxide. Nitric oxide (NO) is an essential regulatory molecule in humans and other animals that helps control constriction and relaxation of blood vessels, thereby regulating the flow of blood throughout the organism. It has been postulated that Hb transports NO in blood as a nitrosothiol at Cys93 of the β-globin chain of Hb and then releases NO upon heme deoxygenation in capillaries. This project uses native top-down MS to identify diagnostic signals from S-nitrosohemoglobin (SNO-Hb). Native top-down MS was used to analyze a series of SNO-Hb samples treated with increasing concentrations of the NO donor SNO-Cys. The data set was analyzed to identify correlations between top-down fragmentation patterns and the relative quantity of SNO-Hb compared to Hb in a mixture. Signal intensity in both raw and deconvoluted spectra were analyzed using a variety of methods including principal components analysis (PCA) and comparisons of intensity deviations from computed median absolute deviation (MAD) values across multiple spectra. Native and top-down experiments were performed using a UHMR Orbitrap MS instrument. Previous studies have analyzed SNO-Hb using both intact and tryptic digest methods, however these previous studies reported challenges in the analysis of SNO-Hb caused by dissociation of the unstable S-nitroso bond. Dissociation of the NO can lead to radical-induced dissociation, further complicating native and top-down results. To address the challenge of interpreting this data, we used a combination of statistical analysis workflows to seek to identify diagnostic signals corresponding to SNO-Hb fragments. Both deconvoluted data sets and raw spectra were analyzed independently to identify common features. The relative intensity values of the diagnostic fragments may enable future quantitative studies of SNO-Hb from biological samples.