RaSs the RNA-seq simulator (2013)

Undergraduates: Zhe Wang, Shunping Huang

Faculty Advisor: Wei Wang
Department: Computer Science

---

RaSs, a RNA-seq simulator, concretely mimics each step in the known sequencing procedure and applies general models on position-based effects that are not easily obtainable by researchers. It generates large volumes of tunable data sets for benchmarking genome recovery algorithm in the field of bio-informatics. A particular advantage of using RaSs is- it supports more than 20 input parameters representing different biology features. Also, our program is considered quite efficient as we can finish processing 1-2GB input data in half an hour.
RaSs operates in two stages: read generation and read modification. The key component is the algorithm mapping between reference chromosome and target chromosome, as insertion, deletion and substitution of base pairs will make the algorithm hard to behave 100% correctly. According to our two weeks' comprehensive testing, our mapping algorithm is correct for 100% test cases.