Recent developments in sequencing technologies have created new opportunities to generate high-throughput biological data at an affordable price. Such high-throughput data needs immense computational resources for performing transcript assembly. Further, a high-end storage facility is needed to store the analyzed data and raw data. Here comes the need for centralized repositories to store such mountains of raw and analyzed data. Hence, it is of utmost importance to ensure data privacy for storing the data while performing transcript assembly. In this paper, we have developed a protocol named SecDATA which performs de novo transcript assembly ensuring data security. It consists of two modules. The first module deals with a framework for secured access and storage of data. The novelty of the first module lies in the employment of distributed ledger technology for data storage that ensures the privacy of the data. The second module deals with the development of an optimized graph-based method for de novo transcript assembly. We have compared our results with the state-of-art method de Bruijn graph and the popular pipeline Trinity, for transcript reconstruction, and our protocol outperforms them.

SecDATA: Secure Data Access and de novo Transcript Assembly protocol - To meet the challenge of reliable NGS data analysis