Development Of Visual RNA-Seq Data Analysis Platformbased On Web

With the development of high-throughput second generation sequencing technology, more and more species and samples complete sequencing, sequencing cost further reduces, and biology research has entered the era of big data. Transcriptome studies based on high-throughput second generation sequencing also got a huge leap: as an important and mature analysis method in transcriptome research, the RNA- seq is widely used in quantitative analysis of gene expression, alternative splicing variance analysis, looking for a new transcript and so on. Extracting the information of transcriptome sequencing data is no longer a problem for biological scientists, but how to efficiently and reasonably analyze massive amounts of RNA-seq data in exponential growth has become the bottleneck of biological research.There have been a lot of RNA- seq analysis software and platforms in recent years, but there exist many problems, such as most platforms are integrating various third-party software, which results in nonstandard and not unified callings. Also many platforms can only start from a complete program and cannot from any step. And a lot of software’s visualization effect is poor. Scientists who are not familiar with bioinformation don’t know which kind of tool to choose for specific analysis. Even if scientists know the tool choice, complexity of operation and debugging parameters also consume a lot of time cost. Especially when doing comprehensive analysis, software and too many modules make a lot of trouble to analysis. Otherwise for industrialization, with personalized sequencing, cloud computing, and the advent of the era of big data, analysis software itself may be not the technical difficulty. How to realize rapid analysis and storage of massive sequencing data, multiple projects’ management, tasks scheduling and automatic interpretation of results, change sequencing data analysis multipoint deployment into web-side uniform distribution automation process management, and realize the intelligent analysis of cloud computing process becomes the key to next breakthrough of industrialization.Our study writes a user friendly local platform based on the Java language unified format. The platform integrates some mainstream and high quality software in various analysis process of RNA- seq, and further iterates the platform to web side, realizing convenient, fast, efficient and the visualized RNA- seq analysis process in the cloud. The web-side RNA- seq analysis platform further makes biological scientists no longer be tied to messy software operation when doing transcriptome sequencing analysis, helps them to realize the remote ‘one-stop’ fool visualization of RNA- seq and other sequencing data analysis and lets them to put more focus on solving biological problems and finding biological significance.In industrialization, some specific experimental analysis case in the past have verified the operability and stability of the platform, the integrative design allows that analysts don’t need to deeply understand data analysis, integrative samples, projects and task management system can easily manage vast amounts of data, and visually display the results. In the agricultural varieties screening and personalized medicine etc. sequencing large-scale industrialization era, this platform as one of the few current domestic sequencing analysis platforms, plays a pioneering role in the field of sequencing data analysis and processing and promotes sequencing industry.