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Exercise #3: BWA-MEM (and Tophat2) - Human mRNA-seq
Obviously, bioinformatics is a viciously cutthroat world. Consequently, after Bowtie2 came out with a local alignment option, it wasn't long before BWA generated their own local-aligner called BWA-MEM (for Maximal Exact Matches). This aligner is very, very nice because it incorporates a lot of the simplicity of using BWA with the complexities of local alignment. This functionality, while enabling the alignment of datasets like the mirbase data we just examined, also permits more complex alignments, such as that of spliced mRNAs. In a long RNA-seq experiment, reads will (at some frequency) span a splice junction themselves, or a pair of reads in a paired-end library will fall on either side of a splice junction. We want to be able to align reads that do this for many reasons, from accurate transcript quantification to novel fusion transcript discovery. Thus, our last exercise will be the alignment of a human LONG RNA-seq dataset composed (by design) almost exclusively of reads that cross splice junctions.
Future Directions