Future movie and gaming industries will employ more and more accurate and numerically reliable methods for animations and rendering, such as the Finite Element Method for solid mechanics, or the Lattice-Boltzmann Method for fluids.
These methods are employed for simulating Carbon Nanotubes materials (sindy), interesting materials for several engineering fields (e.g., aerospace, clothing), animating solid objects (transport), and fluid rendering (mph).
Third-generation mobile genetic sequencing technologies, including Oxford Nanopore's MinION and SmidgION, fit in the palm of a hand and only require a USB outlet. Unfortunately, the development of data analysis tools for these technologies is in a nascent stage, impeding on the portability of these devices.
As genetic sequences require GBs if not TBs of data, we need to address scalability and portability issues, producing software that can, from a smartphone to a workstation (libseq), perform efficiently with limited RAM (nanopal).
This work presents a novel error correction algorithm based on k-mer strings with their associated overlap graph, along with an open-source, multi-threaded, implementation. The algorithm, named HErCoOl (High-throughput Error Correction by Oligomers), needs minimal tuning, only an overall error rate and—optionally—information about the genome sizes.
This work proposes an error correction method based on the de Bruijn graph that permits its execution on Gigabyte-sized data sets using normal desktop computers. The implementation makes extensive use of hashing techniques, and implements an A* algorithm for optimal error correction, minimizing the distance between an erroneous read and its possible replacement with the Needleman-Wunsch score.