Due to complexity of RNA transcripts expressed in any given cell or tissue, the assembly of de novo transcriptomes still represents a computational challenge when compared to genome assemblies. A number of modern transcriptome assembly algorithms have been developed to meet this challenge, and each of them have their own strengths and weaknesses dependent on the transcript abundance and complexity of the biological sample that is sequenced. As such, we are seeking to develop a transcriptome assembly pipeline in which multiple transcriptomes are generated, merged, and then redundancies are filtered out to produce a final transcriptome that should contain full length sequences of all transcripts. However, it is almost impossible to evaluate the efficacies of such novel assembly pipelines using short read sequencing data derived from biological samples due to not knowing a priori the transcript abundance and complexity. Thus, to test our pipelines we developed RAFTS. This tool is used to generate simulated short read sequencing datasets using annotated genomic data from model species.