@article {1230,
	title = {A new parallel pipeline for DNA methylation analysis of long reads datasets.},
	journal = {BMC bioinformatics},
	volume = {18},
	year = {2017},
	month = {2017 Mar 09},
	pages = {161},
	abstract = {BACKGROUND: DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. RESULTS: In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while yielding a better level of sensitivity, particularly for datasets composed of long reads. This strategy can be exported to other methylation, DNA and RNA analysis tools. CONCLUSIONS: The developed software tool achieves execution times one order of magnitude shorter than the existing tools, while yielding equal sensitivity for short reads and even better sensitivity for long reads.},
	keywords = {Methyl-Seq, NGS},
	issn = {1471-2105},
	doi = {10.1186/s12859-017-1574-3},
	url = {http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1574-3},
	author = {Olanda, Ricardo and P{\'e}rez, Mariano and Ordu{\~n}a, Juan M and T{\'a}rraga, Joaqu{\'\i}n and Joaqu{\'\i}n Dopazo}
}
@article {1195,
	title = {HPG pore: an efficient and scalable framework for nanopore sequencing data.},
	journal = {BMC bioinformatics},
	volume = {17},
	year = {2016},
	month = {2016},
	pages = {107},
	abstract = {BACKGROUND: The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION{\texttrademark} from Oxford Nanopore Technologies, is a USB-connected, portable device that allows real-time DNA analysis. In addition, other new instruments are expected to be released soon, which promise to outperform the current short-read technologies in terms of throughput. Despite the flood of data expected from this technology, the data analysis solutions currently available are only designed to manage small projects and are not scalable. RESULTS: Here we present HPG Pore, a toolkit for exploring and analysing nanopore sequencing data. HPG Pore can run on both individual computers and in the Hadoop distributed computing framework, which allows easy scale-up to manage the large amounts of data expected to result from extensive use of nanopore technologies in the future. CONCLUSIONS: HPG Pore allows for virtually unlimited sequencing data scalability, thus guaranteeing its continued management in near future scenarios. HPG Pore is available in GitHub at http://github.com/opencb/hpg-pore .},
	keywords = {hadoop, HPC, nanopore, NGS},
	issn = {1471-2105},
	doi = {10.1186/s12859-016-0966-0},
	url = {http://www.biomedcentral.com/1471-2105/17/107},
	author = {T{\'a}rraga, Joaqu{\'\i}n and Gallego, Asunci{\'o}n and Arnau, Vicente and Medina, Ignacio and Dopazo, Joaquin}
}
@article {1129,
	title = {Babelomics 5.0: functional interpretation for new generations of genomic data.},
	journal = {Nucleic acids research},
	volume = {43},
	number = {W1},
	year = {2015},
	month = {2015 Apr 20},
	pages = {W117-W121},
	abstract = {Babelomics has been running for more than one decade offering a user-friendly interface for the functional analysis of gene expression and genomic data. Here we present its fifth release, which includes support for Next Generation Sequencing data including gene expression (RNA-seq), exome or genome resequencing. Babelomics has simplified its interface, being now more intuitive. Improved visualization options, such as a genome viewer as well as an interactive network viewer, have been implemented. New technical enhancements at both, client and server sides, makes the user experience faster and more dynamic. Babelomics offers user-friendly access to a full range of methods that cover: (i) primary data analysis, (ii) a variety of tests for different experimental designs and (iii) different enrichment and network analysis algorithms for the interpretation of the results of such tests in the proper functional context. In addition to the public server, local copies of Babelomics can be downloaded and installed. Babelomics is freely available at: http://www.babelomics.org.},
	keywords = {babelomics, data integration, gene set analysis, interactome, network analysis, NGS, RNA-seq, Systems biology, transcriptomics},
	issn = {1362-4962},
	doi = {10.1093/nar/gkv384},
	url = {http://nar.oxfordjournals.org/content/43/W1/W117},
	author = {Alonso, Roberto and Salavert, Francisco and Garcia-Garcia, Francisco and Carbonell-Caballero, Jos{\'e} and Bleda, Marta and Garc{\'\i}a-Alonso, Luz and Sanchis-Juan, Alba and Perez-Gil, Daniel and Marin-Garcia, Pablo and S{\'a}nchez, Rub{\'e}n and Cubuk, Cankut and Hidalgo, Marta R and Amadoz, Alicia and Hernansaiz-Ballesteros, Rosa D and Alem{\'a}n, Alejandro and T{\'a}rraga, Joaqu{\'\i}n and Montaner, David and Medina, Ignacio and Dopazo, Joaquin}
}
@article {1162,
	title = {Concurrent and Accurate Short Read Mapping on Multicore Processors.},
	journal = {IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM},
	volume = {12},
	year = {2015},
	month = {2015 Sep-Oct},
	pages = {995-1007},
	abstract = {We introduce a parallel aligner with a work-flow organization for fast and accurate mapping of RNA sequences on servers equipped with multicore processors. Our software, [Formula: see text] ([Formula: see text] is an open-source application. The software is available at http://www.opencb.org, exploits a suffix array to rapidly map a large fraction of the RNA fragments (reads), as well as leverages the accuracy of the Smith-Waterman algorithm to deal with conflictive reads. The aligner is enhanced with a careful strategy to detect splice junctions based on an adaptive division of RNA reads into small segments (or seeds), which are then mapped onto a number of candidate alignment locations, providing crucial information for the successful alignment of the complete reads. The experimental results on a platform with Intel multicore technology report the parallel performance of [Formula: see text], on RNA reads of 100-400 nucleotides, which excels in execution time/sensitivity to state-of-the-art aligners such as TopHat 2+Bowtie 2, MapSplice, and STAR.},
	keywords = {HPC, NGS, short real mapping},
	issn = {1557-9964},
	doi = {10.1109/TCBB.2015.2392077},
	url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=\&arnumber=7010005},
	author = {Martinez, Hector and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Barrachina, Sergio and Castillo, Maribel and Dopazo, Joaquin and Quintana-Orti, Enrique S}
}
@article {1149,
	title = {A Parallel and Sensitive Software Tool for Methylation Analysis on Multicore Platforms.},
	journal = {Bioinformatics (Oxford, England)},
	volume = {31},
	number = {19},
	year = {2015},
	month = {2015 Jun 10},
	pages = {3130-3138},
	abstract = {MOTIVATION: DNA methylation analysis suffers from very long processing time, since the advent of Next-Generation Sequencers (NGS) has shifted the bottleneck of genomic studies from the sequencers that obtain the DNA samples to the software that performs the analysis of these samples. The existing software for methylation analysis does not seem to scale efficiently neither with the size of the dataset nor with the length of the reads to be analyzed. Since it is expected that the sequencers will provide longer and longer reads in the near future, efficient and scalable methylation software should be developed. RESULTS: We present a new software tool, called HPG-Methyl, which efficiently maps bisulfite sequencing reads on DNA, analyzing DNA methylation. The strategy used by this software consists of leveraging the speed of the Burrows-Wheeler Transform to map a large number of DNA fragments (reads) rapidly, as well as the accuracy of the Smith-Waterman algorithm, which is exclusively employed to deal with the most ambiguous and shortest reads. Experimental results on platforms with Intel multicore processors show that HPGMethyl significantly outperforms in both execution time and sensitivity state-of-the-art software such as Bismark, BS-Seeker or BSMAP, particularly for long bisulfite reads. AVAILABILITY: Software in the form of C libraries and functions, together with instructions to compile and execute this software. Available by sftp to anonymous@clariano.uv.es (password "anonymous"). CONTACT: Juan.Orduna@uv.es.},
	keywords = {BS-seq, HPC, methylation, NGS},
	issn = {1367-4811},
	doi = {10.1093/bioinformatics/btv357},
	url = {http://bioinformatics.oxfordjournals.org/content/31/19/3130.long},
	author = {T{\'a}rraga, Joaqu{\'\i}n and P{\'e}rez, Mariano and Ordu{\~n}a, Juan M and Duato, Jos{\'e} and Medina, Ignacio and Joaqu{\'\i}n Dopazo}
}
@article {1076,
	title = {Acceleration of short and long DNA read mapping without loss of accuracy using suffix array.},
	journal = {Bioinformatics (Oxford, England)},
	volume = {30},
	year = {2014},
	month = {2014 Aug 20},
	pages = {3396-3398},
	abstract = {HPG Aligner applies suffix arrays for DNA read mapping. This implementation produces a highly sensitive and extremely fast mapping of DNA reads that scales up almost linearly with read length. The approach presented here is faster (over 20x for long reads) and more sensitive (over 98\% in a wide range of read lengths) than the current, state-of-the-art mappers. HPG Aligner is not only an optimal alternative for current sequencers but also the only solution available to cope with longer reads and growing throughputs produced by forthcoming sequencing technologies.},
	keywords = {NGS, short read mapping. HPC. suffix arrays},
	issn = {1367-4811},
	doi = {10.1093/bioinformatics/btu553},
	url = {http://bioinformatics.oxfordjournals.org/content/early/2014/08/19/bioinformatics.btu553.long},
	author = {T{\'a}rraga, Joaqu{\'\i}n and Arnau, Vicente and Martinez, Hector and Moreno, Raul and Cazorla, Diego and Salavert-Torres, Jos{\'e} and Blanquer-Espert, Ignacio and Joaqu{\'\i}n Dopazo and Medina, Ignacio}
}
