HGVA: the Human Genome Variation Archive. - Lopez, Javier; Coll, Jacobo; Haimel, Matthias; Kandasamy, Swaathi; Tárraga, Joaquín; Furio-Tari, Pedro; Bari, Wasim; Bleda, Marta; Rueda, Antonio; Gräf, Stefan; Rendon, Augusto; Dopazo, Joaquin; et al. (Nucleic Acids Res, 2017)
High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic data for key reference projects in a clean, fast and integrated fashion. HGVA provides an efficient and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries in Python, Java and JavaScript for fast programmatic access to its knowledge base. HGVA calculates population frequencies for these projects and enriches their data with variant annotation provided by CellBase, a rich and fast annotation solution. HGVA serves as a proof-of-concept of the genome analysis developments being carried out by the University of Cambridge together with UK's 100 000 genomes project and the National Institute for Health Research BioResource Rare-Diseases, in particular, deploying open-source for Computational Biology (OpenCB) software platform for storing and analyzing massive genomic datasets.
Keywords: Genetic Variation; Genome, Human; Humans; Internet; Software; User-Computer Interface

VISMapper: ultra-fast exhaustive cartography of viral insertion sites for gene therapy. - Juanes, José M; Gallego, Asunción; Tárraga, Joaquín; Chaves, Felipe J; Marin-Garcia, Pablo; Medina, Ignacio; Arnau, Vicente; Dopazo, Joaquin (BMC Bioinformatics, 2017)
BACKGROUND: The possibility of integrating viral vectors to become a persistent part of the host genome makes them a crucial element of clinical gene therapy. However, viral integration has associated risks, such as the unintentional activation of oncogenes that can result in cancer. Therefore, the analysis of integration sites of retroviral vectors is a crucial step in developing safer vectors for therapeutic use. RESULTS: Here we present VISMapper, a vector integration site analysis web server, to analyze next-generation sequencing data for retroviral vector integration sites. VISMapper can be found at: http://vismapper.babelomics.org . CONCLUSIONS: Because it uses novel mapping algorithms VISMapper is remarkably faster than previous available programs. It also provides a useful graphical interface to analyze the integration sites found in the genomic context.
Keywords: Base Sequence; Genetic Therapy; Genetic Vectors; High-Throughput Nucleotide Sequencing; Humans; Internet; User-Computer Interface; Virus Integration

Fast inexact mapping using advanced tree exploration on backward search methods. - Salavert, José; Tomás, Andrés; Tárraga, Joaquín; Medina, Ignacio; Dopazo, Joaquin; Blanquer, Ignacio (BMC Bioinformatics, 2015)
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

Inferring the functional effect of gene expression changes in signaling pathways. - Sebastián-Leon, Patricia; Carbonell, José; Salavert, Francisco; Sánchez, Rubén; Medina, Ignacio; Dopazo, Joaquin (Nucleic Acids Res, 2013)
Signaling pathways constitute a valuable source of information that allows interpreting the way in which alterations in gene activities affect to particular cell functionalities. There are web tools available that allow viewing and editing pathways, as well as representing experimental data on them. However, few methods aimed to identify the signaling circuits, within a pathway, associated to the biological problem studied exist and none of them provide a convenient graphical web interface. We present PATHiWAYS, a web-based signaling pathway visualization system that infers changes in signaling that affect cell functionality from the measurements of gene expression values in typical expression microarray case-control experiments. A simple probabilistic model of the pathway is used to estimate the probabilities for signal transmission from any receptor to any final effector molecule (taking into account the pathway topology) using for this the individual probabilities of gene product presence/absence inferred from gene expression values. Significant changes in these probabilities allow linking different cell functionalities triggered by the pathway to the biological problem studied. PATHiWAYS is available at: http://pathiways.babelomics.org/.
Keywords: Animals; Humans; Internet; Mice; Models, Statistical; Receptors, Cell Surface; Signal Transduction; Software; Transcriptome

Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments. - García-Alonso, Luz; Alonso, Roberto; Vidal, Enrique; Amadoz, Alicia; De Maria, Alejandro; Minguez, Pablo; Medina, Ignacio; Dopazo, Joaquin (Nucleic Acids Res, 2012)
Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein-protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at http://www.babelomics.org) based on HTML5 technologies is also provided to run the algorithm and represent the network.
Keywords: Bipolar Disorder; Fanconi Anemia; Gene Regulatory Networks; Genes, Neoplasm; Genome-Wide Association Study; Genomics; Humans; Protein Interaction Mapping

Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung's disease. - Fernández, Raquel Ma; Bleda, Marta; Núñez-Torres, Rocío; Medina, Ignacio; Luzón-Toro, Berta; García-Alonso, Luz; Torroglosa, Ana; Marbà, Martina; Enguix-Riego, Ma Valle; Montaner, David; Antiňolo, Guillermo; Dopazo, Joaquin; et al. (Orphanet J Rare Dis, 2012)
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'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

Whole-genome bisulfite DNA sequencing of a DNMT3B mutant patient. - Heyn, Holger; Vidal, Enrique; Sayols, Sergi; Sanchez-Mut, Jose V; Moran, Sebastian; Medina, Ignacio; Sandoval, Juan; Simó-Riudalbas, Laia; Szczesna, Karolina; Huertas, Dori; Gatto, Sole; Matarazzo, Maria R; et al. (Epigenetics, 2012)
The immunodeficiency, centromere instability and facial anomalies (ICF) syndrome is associated to mutations of the DNA methyl-transferase DNMT3B, resulting in a reduction of enzyme activity. Aberrant expression of immune system genes and hypomethylation of pericentromeric regions accompanied by chromosomal instability were determined as alterations driving the disease phenotype. However, so far only technologies capable to analyze single loci were applied to determine epigenetic alterations in ICF patients. In the current study, we performed whole-genome bisulphite sequencing to assess alteration in DNA methylation at base pair resolution. Genome-wide we detected a decrease of methylation level of 42%, with the most profound changes occurring in inactive heterochromatic regions, satellite repeats and transposons. Interestingly, transcriptional active loci and ribosomal RNA repeats escaped global hypomethylation. Despite a genome-wide loss of DNA methylation the epigenetic landscape and crucial regulatory structures were conserved. Remarkably, we revealed a mislocated activity of mutant DNMT3B to H3K4me1 loci resulting in hypermethylation of active promoters. Functionally, we could associate alterations in promoter methylation with the ICF syndrome immunodeficient phenotype by detecting changes in genes related to the B-cell receptor mediated maturation pathway.
Keywords: B-Lymphocytes; Cell Line, Transformed; Child, Preschool; DNA (Cytosine-5-)-Methyltransferases; DNA Methylation; Epigenesis, Genetic; Face; Female; Genome, Human; High-Throughput Nucleotide Sequencing; Humans; Immunologic Deficiency Syndromes; mutation; Primary Immunodeficiency Diseases; Sequence Analysis, DNA; Sulfites

Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. - Medina, Ignacio; Montaner, David; Bonifaci, Núria; Pujana, Miguel Angel; Carbonell, José; Tárraga, Joaquín; Al-Shahrour, Fátima; Dopazo, Joaquin (Nucleic Acids Res, 2009)
Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/.
Keywords: Biological Phenomena; Breast Neoplasms; Female; Genes; Genetic Variation; Genome-Wide Association Study; Humans; Polymorphism, Single Nucleotide; Software; User-Computer Interface

Joint annotation of coding and non-coding single nucleotide polymorphisms and mutations in the SNPeffect and PupaSuite databases. - Reumers, Joke; Conde, Lucia; Medina, Ignacio; Maurer-Stroh, Sebastian; Van Durme, Joost; Dopazo, Joaquin; Rousseau, Frederic; Schymkowitz, Joost (Nucleic Acids Res, 2008)
Single nucleotide polymorphisms (SNPs) are, together with copy number variation, the primary source of variation in the human genome. SNPs are associated with altered response to drug treatment, susceptibility to disease and other phenotypic variation. Furthermore, during genetic screens for disease-associated mutations in groups of patients and control individuals, the distinction between disease causing mutation and polymorphism is often unclear. Annotation of the functional and structural implications of single nucleotide changes thus provides valuable information to interpret and guide experiments. The SNPeffect and PupaSuite databases are now synchronized to deliver annotations for both non-coding and coding SNP, as well as annotations for the SwissProt set of human disease mutations. In addition, SNPeffect now contains predictions of Tango2: an improved aggregation detector, and Waltz: a novel predictor of amyloid-forming sequences, as well as improved predictors for regions that are recognized by the Hsp70 family of chaperones. The new PupaSuite version incorporates predictions for SNPs in silencers and miRNAs including their targets, as well as additional methods for predicting SNPs in TFBSs and splice sites. Also predictions for mouse and rat genomes have been added. In addition, a PupaSuite web service has been developed to enable data access, programmatically. The combined database holds annotations for 4,965,073 regulatory as well as 133,505 coding human SNPs and 14,935 disease mutations, and phenotypic descriptions of 43,797 human proteins and is accessible via http://snpeffect.vib.be and http://pupasuite.bioinfo.cipf.es/.
Keywords: Amino Acid Substitution; Animals; Databases, Genetic; Genetic Diseases, Inborn; HSP70 Heat-Shock Proteins; Humans; Internet; Mice; MicroRNAs; mutation; Polymorphism, Single Nucleotide; Proteins; Rats; RNA Splice Sites; Transcription Factors

FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. - Al-Shahrour, Fátima; Minguez, Pablo; Tárraga, Joaquín; Medina, Ignacio; Alloza, Eva; Montaner, David; Dopazo, Joaquin (Nucleic Acids Res, 2007)
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

ISACGH: a web-based environment for the analysis of Array CGH and gene expression which includes functional profiling. - Conde, Lucia; Montaner, David; Burguet-Castell, Jordi; Tárraga, Joaquín; Medina, Ignacio; Al-Shahrour, Fátima; Dopazo, Joaquin (Nucleic Acids Res, 2007)
We present the ISACGH, a web-based system that allows for the combination of genomic data with gene expression values and provides different options for functional profiling of the regions found. Several visualization options offer a convenient representation of the results. Different efficient methods for accurate estimation of genomic copy number from array-CGH hybridization data have been included in the program. Moreover, the connection to the gene expression analysis package GEPAS allows the use of different facilities for data pre-processing and analysis. A DAS server allows exporting the results to the Ensembl viewer where contextual genomic information can be obtained. The program is freely available at: http://isacgh.bioinfo.cipf.es or within http://www.gepas.org.
Keywords: Animals; Cluster Analysis; Computational Biology; Computer Graphics; Gene Expression Profiling; Humans; Internet; Models, Genetic; Nucleic Acid Hybridization; Oligonucleotide Array Sequence Analysis; Programming Languages; Software; Systems Integration; User-Computer Interface