The rapid expansion in the quantity and quality of RNA-Seq data requires the 
development of sophisticated high-performance bioinformatics tools capable of 
rapidly transforming this data into meaningful information that is easily 
interpretable by biologists. Currently available analysis tools are often not 
easily installed by the general biologist and most of them lack inherent 
parallel processing capabilities widely recognized as an essential feature of 
next-generation bioinformatics tools. We present here a user-friendly and fully 
automated RNA-Seq analysis pipeline (R-SAP) with built-in multi-threading 
capability to analyze and quantitate high-throughput RNA-Seq datasets. R-SAP 
follows a hierarchical decision making procedure to accurately characterize 
various classes of transcripts and achieves a near linear decrease in data 
processing time as a result of increased multi-threading. In addition, RNA 
expression level estimates obtained using R-SAP display high concordance with 
levels measured by microarrays.