Life Sciences

jModelTest

This code is being developed jointly with the staff from the Departamento de Genética, Bioquímica e Inmunología, Universidad de Vigo (Spain) and CESGA (Spain).

The estimation of the evolutionary relationships between DNA sequences obtained from different individuals or species has important biomedical implications. Nowadays, phylogenetic trees are use to predict gene function, to track tumour mutations or to monitor the geographical spread of pathogens, for example. An essential step of the phylogenetic analysis is the selection of appropriate models of nucleotide substitution. During the last years, different statistical selection strategies have been proposed and several programs have been developed to carry out this task; among them, the most popular has been Modeltest [1], which has been superseded by its Java implementation, jModelTest [2].

jModelTest can be freely downloaded from http://darwin.uvigo.es and allows for the definition of restricted sets of up to 88 candidate models. Among other functionalities, jModelTest is able to implement customizable hierarchical and dynamic likelihood ratio tests, provide a rank of models according to the Akaike Information Criterion, to the Bayesian Information Criterion or to a decision theoretic performance-based approach, calculate the relative importance of every model parameter and compute model-averaged estimates of these, including a model-averaged estimate of the tree topology.

By this work, a MPI version to be run on local clusters and a DRMAA release to be executed on Grid or local clusters too are available.

[1] D. Posada, K.A. Crandall. "Modeltest: testing the model of DNA substitution". Bioinformatics 14, 817-818 (1998)
[2] D. Posada. "jModelTest: Phylogenetic Model Averaging". Mol. Biol. Evol. 25, 1253-1256 (2008)

This work has already been presented at:
Cracow Grid Workshop (Cracow, Nov 2011 - we warmly thank Dr. T. Glatard for including jMT in the LSGC presentation)
SoIBio Conference (Termas de Chillán, September 2010)
GISELA KoM (San Luis Potosí, September 2010)
Healthgrid Conference (Paris, June 2010)
IberGrid Conference (Braga, May 2010) 

ProtTest3

This code is being developed jointly with the staff from the Departamento de Genética, Bioquímica e Inmunología, Universidad de Vigo (Spain), and the Grupo de Arquitectura de Computadores, Universidad de A Coruña (Spain).

The statistical study of protein evolution and phylogenetic inference relies on appropriate models of amino acid replacement. In this sense, ProtTest [1] is a widely used tool for the selection of the best-fit model of evolution, among a set of candidate models, for a given protein sequence alignment. For large data sets, the calculations carried out by this program can be too expensive for many users, so a High Performance Computing (HPC) version of ProtTest that can be executed on parallel in multi-core desktops and clusters, called ProtTest3 [2], was lately released including new features and extended capabilities.

Now, a new release based on ProtTest3 code has been ported to Grid computing using DRMAA. This work should facilitate the use of the code on a broader scale.

[1] F. Abascal, R. Zardoya, D. Posada. "ProtTest: selection of best-fit models of protein evolution", Bioinformatics 21, 2104-2105 (2005)
[2] D. Darriba, G.L. Taboada, R. Doallo, D. Posada. "ProtTest 3: fast selection of best-fit models of protein evolution". Bioinformatics 27, 1164-1165 (2011)

This work has already been presented at:
Cracow Grid Workshop (Cracow, Nov 2011 - we warmly thank Dr. T. Glatard for including PT in the LSGC presentation)
SoIBio Conference (Florianopolis, October 2011)
Healthgrid Conference (Bristol, June 2011)

PhyloGrid

This code is being developed jointly with the staff from the Fundación IDEA (Venezuela) in the framework of the EELA-2 Project

The determination of the evolution history of different species is nowadays one of the most exciting challenges that are currently emerging in computational Biology. In this framework, Phylogeny is able to determine the relationship among the species and, in this way, to understand the influence between hosts and virus. As an example we can mention the AIDS disease.

In this code we are working on the development of a workflow based on Taverna [1] which is going to be implemented for calculations in Phylogeny by means of the MrBayes tool [2]. It has a friendly interface developed with the Gridsphere framework [3]. The user is able to define the parameters needed to perform the Bayesian calculation, determine the model of evolution as well as do a multiple alignment of the sequences previously to the final result. To do this, no knowledge from his/her side about the computational procedure is required.

[1] http://taverna.sourceforge.net
[2] http://www.mrbayes.net
[3] http://www.gridsphere.org/gridsphere/gridsphere/guest/home/r

This work has already been presented at:
HealthGrid Conference (Paris, June 2010)
EELA-2 Conference (Choroní, November 2009)
HealthGrid Conference (Berlin, July 2009)
IWPACBB (Salamanca, June 2009)
EELA-2 Conference (Bogota, February 2009)
UK All-Hands Meeting (Edinburgh, September 2008)
Ibergrid Conference (Porto, May 2008)

GAMOS

This code is being developed jointly with the staff from the Electronic and Automatic Division of CIEMAT in the framework of the EELA-2 Project

GAMOS [1] (the Geant4-based Architecture for Medicine-Oriented Simulations) is a framework based on GEANT4 [2], specialized for the simulation of medical applications, in both fields of medical image (PET/SPECT) and radiation therapy (teletherapy and brachytherapy). It offers a simple user interface covering the most common needs of a medical application, so that simulations with Geant4 can be carried out without having to code in C++. At the same time, if the user has a special request, it permits to add new functionalities in a simple way, thanks to the utilization of the technology of plugins. It also comes with an extensive set of tools that allows the user to get a detailed understanding of the simulation with a minimal effort. Two main use cases can be identified. The first one refers to the simulation of detectors in the field of the medical image (PET/SPECT) to obtain a detailed understanding of the capacities of a detector. In the field of the radiotherapy with electrons or photons, the flexibility of GAMOS as well as the implementation of diverse techniques of variance reduction, makes it very adequate for the simulation of the most modern accelerators used in the hospitals nowadays. The possibility to interact with the DICOM format of medical image allows carrying out in a simple way the calculations of dose in patients from the images obtained by the diverse apparatuses of a hospital (PET/CT/RMN).

[1] The GAMOS tool
[2] The GEANT4 tool 

This work has already been presented at:
GISELA KoM (San Luis Potosí, September 2010)
EELA-2 Conference (Choroní, November 2009)