Further, assisted by the expression profiling analysis, another Tier-3 fusion was predicted in the Providence cohort. Our method also addresses intronic RNA sequences, in recognition of the large amount of intronic Hygromycin B sequence information present in FFPE RNA. Both donor and acceptor pre-mRNAs are built into 5 template sets to filter out reads mapped to mRNA precursors. On the other hand, the introns are selectively included in the expression profiling analysis to take advantage of abundant intronic sequence information. The two different remapping steps by GSNAP were designed to improve the mapping accuracy given the short inset size of FFPE. The success of these FFPE RNA-targeted designs is reflected by the high frequency of TaqMan support rates in the Tier-1 category. Although the cohort based strategy described here was developed with and applied to FFPE tissue and single end RNASeq datasets, it is also relevant to fusion transcript detection in cell lines and fresh frozen samples. Because hospital separations typically contain Isoetharine Mesylate multiple diagnoses, with the primary or principal diagnosis in the first position followed by one or more secondary diagnoses, we abstracted statistics for each of these positions, where available. This was especially important given some recent studies of administrative databases that suggest hospitalizations with HF in the primary position are decreasing, while those with HF coded in secondary diagnostic positions are increasing. Data were independently abstracted by each reviewer who subsequently compared their forms to correct any errors and resolve discrepancies. Single molecule sequencing and other long read approaches aimed at increasing read length are expected to generally improve detection of genomic rearrangements, but the benefit of these improvements for FFPE specimens will be limited due to the short RNA fragments isolated from archived FFPE samples. Rapidly decreasing sequencing costs will enable data collection on more archived FFPE samples, therefore we anticipate that the method presented here will continue to facilitate fusion transcript detection and biomarker discovery in FFPE RNA.