The current GLM-based PSEM framework only considers 9 types of genome sequence context features. To further improve the performances, more informative features associated with sequencing errors should be included and tested. In addition, from the modeling aspect, exploration of the potential to further increase the performances by applying more sophisticated computational models are desired. To better understand its generalizability and adaptiveness, tests on other sequencing technologies, such us SOLiD and Complete Genomics, are necessary. Besides, since the capture assay for the two benchmarks is amplicon-based, hybridization-based approach should be tested to compare the performance profiles.
