Abstract
Recent advances in DNA sequencing have made it possible to sequence the whole transcriptome by massively parallel sequencing, commonly referred as RNA-Seq. RNA-Seq is quickly becoming the technology of choice for transcriptome research and analyses. RNA-Seq allows to reduce the sequencing cost and significantly increase data throughput, but it is computationally challenging to use such RNA-Seq data for reconstructing of full length transcripts and accurately estimate their abundances across all cell types. The common computational problems include: gene and isoform expression level estimation [1], find transcriptome quantification, transcriptome discovery and reconstruction. To solve these problems it is required to have scalable computational tools.