G-DNA (GPU-based DNA aligner) is the first highly parallel solution that has been optimized to process nucleotide reads (DNA/RNA) from modern sequencing machines. Results show that the software is very efficient on both multi-GPU machines and MPI+GPU clusters. It computes scores and shifts for a given set of sequence pairs. It might be used as an efficient aligning tool in de-novo assembly.
G-MSA -- a valuable tool for the MSA problem which is efficient and can be run on a common personal computer equipped with NVIDIA GPU (G80, GT200 or Fermi). Extensive tests show its great speedup in comparison to the T-Coffee method on which it was based whereas the quality of the results remained very high. Moreover, multi-GPU support influences the execution time considerably.
gpu-pairAlign (G-PAS) implements global and semiglobal Needleman-Wunsch, and Smith-Waterman algorithms with a backtracking procedure which is needed to construct the alignment. Our solution performs the alignment of every given sequence pair, which is a required step e.g. for progressive multiple sequence alignment methods, as well as for DNA recognition at the DNA assembly stage. Tests show that the implementation, with performance up to 6.3 GCUPS on a single GPU for affine gap penalties, is very efficient in comparison to other CPU and GPU-based solutions. Moreover, multiple GPUs support with load balancing makes the application very scalable.
For more information see the article in BMC Bioinformatics
G-MAPSEQ is a tool for mapping Next Generation Sequencing reads to the reference genome. The solution connects two basic ideas - fast heuristic to determine candidates for similar pairs of sequences (where one is the read, and the second is a fragment of reference sequence) and exact, ultrafast semiglobal pairwise alignment method which is performed on GPU, to check if the candidates are real mapping positions. G-MAPSEQ supports both: single and pairend reads.