@article {472, title = {Fast inexact mapping using advanced tree exploration on backward search methods.}, journal = {BMC Bioinformatics}, volume = {16}, year = {2015}, month = {2015 Jan 28}, pages = {18}, abstract = {

BACKGROUND: Short sequence mapping methods for Next Generation Sequencing consist on a combination of seeding techniques followed by local alignment based on dynamic programming approaches. Most seeding algorithms are based on backward search alignment, using the Burrows Wheeler Transform, the Ferragina and Manzini Index or Suffix Arrays. All these backward search algorithms have excellent performance, but their computational cost highly increases when allowing errors. In this paper, we discuss an inexact mapping algorithm based on pruning strategies for search tree exploration over genomic data.

RESULTS: The proposed algorithm achieves a 13x speed-up over similar algorithms when allowing 6 base errors, including insertions, deletions and mismatches. This algorithm can deal with 400 bps reads with up to 9 errors in a high quality Illumina dataset. In this example, the algorithm works as a preprocessor that reduces by 55\% the number of reads to be aligned. Depending on the aligner the overall execution time is reduced between 20-40\%.

CONCLUSIONS: Although not intended as a complete sequence mapping tool, the proposed algorithm could be used as a preprocessing step to modern sequence mappers. This step significantly reduces the number reads to be aligned, accelerating overall alignment time. Furthermore, this algorithm could be used for accelerating the seeding step of already available sequence mappers. In addition, an out-of-core index has been implemented for working with large genomes on systems without expensive memory configurations.

}, keywords = {Algorithms, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, Sequence Alignment, Sequence Analysis, DNA, Software}, issn = {1471-2105}, doi = {10.1186/s12859-014-0438-3}, author = {Salavert, Jos{\'e} and Tom{\'a}s, Andr{\'e}s and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Dopazo, Joaquin and Blanquer, Ignacio} } @article {515, title = {Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung{\textquoteright}s disease.}, journal = {Orphanet J Rare Dis}, volume = {7}, year = {2012}, month = {2012 Dec 28}, pages = {103}, abstract = {

Finding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a pathway-based analysis (PBA) has been initially conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung{\textquoteright}s disease. Candidate genes have been further validated in an independent population of 106 trios. The study revealed a strong association of 11 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes. Among the preselected candidates, a total of 4 loci, RASGEF1A, IQGAP2, DLC1 and CHRNA7, related to signal transduction and migration processes, were found to be significantly associated to HSCR. Network analysis also confirms their involvement in the network of already known disease genes. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.

}, keywords = {Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Hirschsprung Disease, Humans, Male}, issn = {1750-1172}, doi = {10.1186/1750-1172-7-103}, author = {Fern{\'a}ndez, Raquel Ma and Bleda, Marta and N{\'u}{\~n}ez-Torres, Roc{\'\i}o and Medina, Ignacio and Luz{\'o}n-Toro, Berta and Garc{\'\i}a-Alonso, Luz and Torroglosa, Ana and Marb{\`a}, Martina and Enguix-Riego, Ma Valle and Montaner, David and Anti{\v n}olo, Guillermo and Dopazo, Joaquin and Borrego, Salud} } @article {944, title = {Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung{\textquoteright}s disease.}, journal = {Orphanet journal of rare diseases}, volume = {7}, year = {2012}, month = {2012 Dec 28}, pages = {103}, abstract = {ABSTRACT: Finding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a pathway-based analysis (PBA) has been initially conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung{\textquoteright}s disease. Candidate genes have been further validated in an independent population of 106 trios. The study revealed a strong association of 11 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes. Among the preselected candidates, a total of 4 loci, RASGEF1A, IQGAP2, DLC1 and CHRNA7, related to signal transduction and migration processes, were found to be significantly associated to HSCR. Network analysis also confirms their involvement in the network of already known disease genes. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.}, issn = {1750-1172}, doi = {10.1186/1750-1172-7-103}, url = {http://www.ojrd.com/content/7/1/103/abstract}, author = {Fern{\'a}ndez, Raquel Ma and Bleda, Marta and N{\'u}{\~n}ez-Torres, Roc{\'\i}o and Medina, Ignacio and Luz{\'o}n-Toro, Berta and Garc{\'\i}a-Alonso, Luz and Torroglosa, Ana and Marb{\`a}, Martina and Enguix-Riego, Ma Valle and Montaner, David and Anti{\v n}olo, Guillermo and Joaqu{\'\i}n Dopazo and Borrego, Salud} } @article {605, title = {FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jul}, pages = {W91-6}, abstract = {

The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.

}, keywords = {Amino Acid Motifs, Animals, Binding Sites, Computational Biology, Gene Expression Profiling, Genes, Genomics, Humans, Internet, Oligonucleotide Array Sequence Analysis, Programming Languages, Software, Systems Integration, Transcription Factors}, issn = {1362-4962}, doi = {10.1093/nar/gkm260}, author = {Al-Shahrour, F{\'a}tima and Minguez, Pablo and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Alloza, Eva and Montaner, David and Dopazo, Joaquin} } @article {17478504, title = {FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments}, journal = {Nucleic Acids Res}, volume = {35}, number = {Web Server issue}, year = {2007}, note = {

Al-Shahrour, Fatima Minguez, Pablo Tarraga, Joaquin Medina, Ignacio Alloza, Eva Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2007 Jul;35(Web Server issue):W91-6. Epub 2007 May 3.

}, pages = {W91-6}, abstract = {

The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.

}, keywords = {babelomics, functional enrichment analysys}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17478504}, author = {Fatima Al-Shahrour and Minguez, P. and Tarraga, J. and Medina, Ignacio and Alloza, E. and Montaner, D. and Dopazo, J.} }