MOTIVATION: The alignment of bisulfite-treated DNA sequences (BS-seq reads) to a 
large genome involves a significant computational burden beyond that required to 
align non-bisulfite-treated reads. In the analysis of BS-seq data, this can 
present an important performance bottleneck that can be mitigated by appropriate 
algorithmic and software-engineering improvements. One strategy is to modify the 
read-alignment algorithms by integrating the logic related to BS-seq alignment, 
with the goal of making the software implementation amenable to optimizations 
that lead to higher speed and greater sensitivity than might otherwise be 
attainable.
RESULTS: We evaluated this strategy using Arioc, a short-read aligner that uses 
GPU (general-purpose graphics processing unit) hardware to accelerate 
computationally-expensive programming logic. We integrated the BS-seq 
computational logic into both GPU and CPU code throughout the Arioc 
implementation. We then carried out a read-by-read comparison of Arioc's 
reported alignments with the alignments reported by well-known CPU-based BS-seq 
read aligners. With simulated reads, Arioc's accuracy is equal to or better than 
the other read aligners we evaluated. With human sequencing reads, Arioc's 
throughput is at least 10 times faster than existing BS-seq aligners across a 
wide range of sensitivity settings.
AVAILABILITY AND IMPLEMENTATION: The Arioc software is available for download at 
https://github.com/RWilton/Arioc. It is released under a BSD open-source 
license.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics 
online.