Overview

As sequencing technologies progress the amount of data produced grows exponentially, shifting the bottleneck of discovery towards the data analysis phase. Here we present an innovative approach that combines reengineering, optimization and parallelization of the algorithms which results in a significant increase of the mapping sensitivity over a wide range of read lengths and substantial shorter runtimes when compared to other NGS mapping solutions currently available. Moreover, our software has been implemented using High-Performance computing (HPC) technologies such as OpenMP for multi-core CPUs, SSE and Nvidia CUDA for GPUs, besides, comparatively, the performance of this approach scales up very efficiently with the number of processors, therefore our implementation is ready to take advantage of new CPUs and GPUs.
Currently three modes are being implemented:
  • dna: we have focused in sensitivity and long reads mapping. First results show that we are able to map INDELS and long reads (>1kb) with high sensitivity and faster than the state of the art software
  • rna: we have focused in sensitivity and long reads mapping. First results show that we are able to map short and long reads (>1kb) with high sensitivity and many times faster than TopHat software
  • bs (bisulfite): under development
  • Homepage: home

Members

Head of the Department: Joaquin Dopazo
Project Manager: Ignacio Medina
Bioinformatician: Ignacio Medina
Scientific Programmer: Hector Martinez, Ignacio Medina, Joaquin Tarraga