GECKO + GECKO-CSB + GECKO-MGV + META-GECKO + GECKO-REFINEMENT
The comparison of genomes is a traditional problem with high memory and CPU time requisites. Those requisites can be reduced redesigning the process and using HPC techniques in its development. We have developed a program for genomes comparison handling long sequences.
GECKO-CSB is able to detect and identify blocks of large rearrangements taking into account repeats, tandem repeats and duplications, starting with the simple collection of ungapped local alignments. To the best of our knowledge, this is the first method to approach the whole process as a coherent workflow, thus outperforming current state-of-the-art software tools, and additionally allowing to classify the type of rearrangement. The results obtained are an important source of information for breakpoints refinement and featuring, as well as for the estimation of the Evolutionary Events frequencies to be used in inter-genome distance proposals, etc.
Web-based, platform-independent tool to analyse results of pairwise and multiple sequences comparison software. The implemented tool (GECKO-MGV) includes the traditional capabilities of this type of software, incorporating the concept of layers from image editing software to represent different comparisons. An innovative feature of GECKO-MGV is the integration of the Evolutionary Events timeline. To extend the functionality of GECKO-MGV, a set of post-processing services has been included.
Set of post-processing tools aimed at improving the taxonomical classification and at providing additional information to enhance metagenomics analyses. The developed tools provide additional proofs in the presence of low-abundant species, information of the mapping quality in coding and noncoding regions, etc.
We propose a method to refine the borders of genomic rearrangements including repeated regions. Instead of removing these repetitions to facilitate computation, we take advantage of them using a consensus alignment sequence of the repeated region in between two blocks. Using the concept of identity vectors for Synteny Blocks (SB) and repetitions, a Finite State Machine is designed to detect transition points in the difference between such vectors. The method does not force the BP to be a region or a point but depends on the alignment transitions within the SBs and repetitions.