Sequencing of RNA (RNA-seq) using next generation sequencing has become the standard approach for profiling the transcriptomic state of a cell. This requires mapping of the sequencing reads to determine their transcriptomic origin.
Recently, we developed a context-based mapping approach, ContextMap, which determines the most likely origin of a read by evaluating the context of the read in the form of alignments of other reads to the same genomic region. In the original implementation, the focus was on improving initial mappings provided by other mapping tools.
Here, we present ContextMap 2.0, an extension of the original ContextMap method, which can also be used as a standalone tool without relying on initial mappings by other tools. We show that it yields highly accurate read mappings and is very robust against sequencing errors. The design of ContextMap 2.0 allows for massively parallelized data processing, resulting in reasonable running times despite the higher complexity of the context-based approach.