Construction Of Proteomics Data Analysis System Based On Cloud Platform

Proteomics has entered the era of big data,as there are continuous improvements of high-throughput mass spectrometry instruments and technical methods.The big data in proteomics provide a lot of data and knowledge sources for the interpretation of the mysteries of life,in-depth understanding of the disease mechanism and precise medicine.However,the rapid development of proteomics data has also brought new challenges to traditional biology laboratories.The lack of standardized metadata processing systems,and poor raw data management system,has greatly impeded the efficiency of proteomics research.In order to solve the above problems,this paper constructed a cloud-based proteome data analysis system based on the Galaxy platform.This system consists of metadata management module,data processing module,data analysis and visualization module and data mining module.In this paper,we firstly,established the module of experimental metadata based on the metadata standard set by HUPO-PSI.And we also deployed the efficient and safe raw data collection module to provide multi-level data transferring and backup system,to ensure data security of proteomics data.Furthermore,we constructed an automated data processing platform based on the Galaxy platform.The data processing platform integrates open source proteomics analysis frameworks and tools including ProteoWizard and TPP,and independently develops a variety of qualitative and quantitative software.This study implements the parallel optimization of above tools.As for efficiently data analysis,this paper builds a user-friendly and easy-to-use proteome data visualization and comprehensive analysis platform based on the B/S architecture using mainstream languages such as R and Python.The platform can visualize and interactively show and analyze proteomics data while supporting joint analysis of multiple sets of data and data mining capabilities based on data collected by Firmiana.The deployment of the application interface makes Firmiana extensible and practical.Based on the datasets collected by this system,we have developed data mining modules and constructed a protein interaction network.To adapt new mass spectrometry based proteomics,we have also developed a series of proteome identification and quantification modules.This study describes the ultra-short dynamic exclusion methods in detail.We have applied both calculations reconstruction of extracted ion chromatogram(XIC)and signal summation of fragment ions on this methods.After applying the algorithms on the methods,quantitative accuracy of proteomes can be effectively improved,demonstrating the practicality and scalability of the system.The study of cloud platform based proteomics data analysis system will be a powerful tool to promote the development of proteomics,facilitate life sciences and human health.