Reductive Analytics on Big MS Data leads to tremendous reduction in time for peptide deduction

In this paper we present a feasibility of using a data-reductive strategy for analyzing big MS data. The proposed method utilizes our reduction algorithm MS-REDUCE and peptide deduction is accomplished using Tide with hiXcorr. Using this approach we were able to process 1 million spectra in under 3 hours. Our results showed that running peptide deduction with smaller amount of selected peaks made the computations much faster and scalable with increasing resolution of MS data. Quality assessment experiments performed on experimentally generated datasets showed good quality peptide matches can be made using the reduced datasets. We anticipate that the proteomics and systems biology community will widely adopt our reductive strategy due to its efficacy and reduced time for analysis.