Asterias: A Parallelized Web-based Suite for the Analysis of Expression and aCGH Data

The analysis of expression and CGH arrays plays a central role in the study of complex diseases, especially cancer, including finding markers for early diagnosis and prognosis, choosing an optimal therapy, or increasing our understanding of cancer development and metastasis. Asterias (http://www.asterias.info) is an integrated collection of freely-accessible web tools for the analysis of gene expression and aCGH data. Most of the tools use parallel computing (via MPI) and run on a server with 60 CPUs for computation; compared to a desktop or server-based but not parallelized application, parallelization provides speed ups of factors up to 50. Most of our applications allow the user to obtain additional information for user-selected genes (chromosomal location, PubMed ids, Gene Ontology terms, etc.) by using clickable links in tables and/or figures. Our tools include: normalization of expression and aCGH data (DNMAD); converting between different types of gene/clone and protein identifiers (IDconverter/IDClight); filtering and imputation (preP); finding differentially expressed genes related to patient class and survival data (Pomelo II); searching for models of class prediction (Tnasas); using random forests to search for minimal models for class prediction or for large subsets of genes with predictive capacity (GeneSrF); searching for molecular signatures and predictive genes with survival data (SignS); detecting regions of genomic DNA gain or loss (ADaCGH). The capability to send results between different applications, access to additional functional information, and parallelized computation make our suite unique and exploit features only available to web-based applications

Asterias: integrated analysis of expression and aCGH data using an open-source, web-based, parallelized software suite

Asterias (http://www.asterias.info) is an open-source, web-based, suite for the analysis of gene expression and aCGH data. Asterias implements validated statistical methods, and most of the applications use parallel computing, which permits taking advantage of multicore CPUs and computing clusters. Access to, and further analysis of, additional biological information and annotations (PubMed references, Gene Ontology terms, KEGG and Reactome pathways) are available either for individual genes (from clickable links in tables and figures) or sets of genes. These applications cover from array normalization to imputation and preprocessing, differential gene expression analysis, class and survival prediction and aCGH analysis. The source code is available, allowing for extention and reuse of the software. The links and analysis of additional functional information, parallelization of computation and open-source availability of the code make Asterias a unique suite that can exploit features specific to web-based environments

(1R,4R,5R)-1,3,4-Triphenyl-7-[(R)-1-phenyl­ethyl]-2-oxa-3,7-diaza­spiro­[4.5]decan-10-one

In the title compound, C33H32N2O2, the polysubstituted piperidine ring adopts a chair conformation. The isoxazolidine ring is in an envelope conformation. In the crystal structure, intra- and inter­molecular C—H⋯π inter­actions involving the phenyl rings are observed

An estimate of the time variation of the O/H radial gradient from planetary nebulae

Radial abundance gradients are a common feature of spiral galaxies, and in the case of the Galaxy both the magnitude of the gradients and their variations are among the most important constraints of chemical evolution models. Planetary nebulae (PN) are particularly interesting objects to study the gradients and their variations. Owing to their bright emission spectra, they can be observed even at large galactocentric distances, and the derived abundances are relatively accurate, with uncertainties of about 0.1 to 0.2 dex, particularly for the elements that are not synthesized in their progenitor stars. On the other hand, as the offspring of intermediate mass stars, with main sequence masses in the interval of 1 to 8 solar masses, they are representative of objects with a reasonable age span. In this paper, we present an estimate of the time variation of the O/H radial gradient in a sample containing over 200 nebulae with accurate abundances. Our results are consistent with a flattening of the O/H gradient roughly from -0.11 dex/kpc to -0.06 dex/kpc during the last 9 Gyr, or from -0.08 dex/kpc to -0.06 dex/kpc during the last 5 Gyr.Comment: 9 pages, 7 encapsulated postscript figures, LaTeX, uses Astronomy and Astrophysics macro aa.cls, graphicx package, to be published in Astronomy and Astrophysics (2002), Also available at: http://www.astro.iag.usp.br/~macie

GeneSrF and varSelRF: a web-based tool and R package for gene selection and classification using random forest

<p>Abstract</p> <p>Background</p> <p>Microarray data are often used for patient classification and gene selection. An appropriate tool for end users and biomedical researchers should combine user friendliness with statistical rigor, including carefully avoiding selection biases and allowing analysis of multiple solutions, together with access to additional functional information of selected genes. Methodologically, such a tool would be of greater use if it incorporates state-of-the-art computational approaches and makes source code available.</p> <p>Results</p> <p>We have developed GeneSrF, a web-based tool, and varSelRF, an R package, that implement, in the context of patient classification, a validated method for selecting very small sets of genes while preserving classification accuracy. Computation is parallelized, allowing to take advantage of multicore CPUs and clusters of workstations. Output includes bootstrapped estimates of prediction error rate, and assessments of the stability of the solutions. Clickable tables link to additional information for each gene (GO terms, PubMed citations, KEGG pathways), and output can be sent to PaLS for examination of PubMed references, GO terms, KEGG and and Reactome pathways characteristic of sets of genes selected for class prediction. The full source code is available, allowing to extend the software. The web-based application is available from <url>http://genesrf2.bioinfo.cnio.es</url>. All source code is available from Bioinformatics.org or The Launchpad. The R package is also available from CRAN.</p> <p>Conclusion</p> <p>varSelRF and GeneSrF implement a validated method for gene selection including bootstrap estimates of classification error rate. They are valuable tools for applied biomedical researchers, specially for exploratory work with microarray data. Because of the underlying technology used (combination of parallelization with web-based application) they are also of methodological interest to bioinformaticians and biostatisticians.</p

Galactic chemical abundance evolution in the solar neighborhood up to the Iron peak

We have developed a detailed standard chemical evolution model to study the evolution of all the chemical elements up to the iron peak in the solar vicinity. We consider that the Galaxy was formed through two episodes of exponentially decreasing infall, out of extragalactic gas. In a first infall episode, with a duration of $\sim$ 1 Gyr, the halo and the thick disk were assembled out of primordial gas, while the thin disk formed in a second episode of infall of slightly enriched extragalactic gas, with much longer timescale. The model nicely reproduces the main observational constraints of the solar neighborhood, and the calculated elemental abundances at the time of the solar birth are in excellent agreement with the solar abundances. By the inclusion of metallicity dependent yields for the whole range of stellar masses we follow the evolution of 76 isotopes of all the chemical elements between hydrogen and zinc. Those results are confronted with a large and recent body of observational data, and we discuss in detail the implications for stellar nucleosynthesis.Comment: 19 pages, 14 figures, submitted to A&

New results on the time variation of the radial abundance gradients from planetary nebulae

New results on the time variation of the radial abundance gradients in the galactic disk are presented on the basis of four different samples of planetary nebulae. These comprise both smaller, homogeneous sets of data, and larger but non-homogeneous samples. Four different chemical elements are considered, namely, O, S, Ar, and Ne. Other objects such as open clusters, cepheids and HII regions are also taken into account. Our analysis support our earlier conclusions in the sense that, on the average, the radial abundance gradients have flattened out during the last 6 to 8 Gyr, with important consequences for models of the chemical evolution of the Galaxy.Comment: 2 pages, 1 figure, LaTeX, To be published in the Proceedings of the IAU Symposium 234: Planetary Nebulae in Our Galaxy and Beyond, ed. M. J. Barlow, R. H. Mende

HumMeth27QCReport: an R package for quality control and primary analysis of Illumina Infinium methylation data

<p>Abstract</p> <p>Background</p> <p>The study of the human DNA methylome has gained particular interest in the last few years. Researchers can nowadays investigate the potential role of DNA methylation in common disorders by taking advantage of new high-throughput technologies. Among these, Illumina Infinium assays can interrogate the methylation levels of hundreds of thousands of CpG sites, offering an ideal solution for genome-wide methylation profiling. However, like for other high-throughput technologies, the main bottleneck remains at the stage of data analysis rather than data production.</p> <p>Findings</p> <p>We have developed <it>HumMeth27QCReport</it>, an R package devoted to researchers wanting to quickly analyse their Illumina Infinium methylation arrays. This package automates quality control steps by generating a report including sample-independent and sample-dependent quality plots, and performs primary analysis of raw methylation calls by computing data normalization, statistics, and sample similarities. This package is available at CRAN repository, and can be integrated in any Galaxy instance through the implementation of ad-hoc scripts accessible at Galaxy Tool Shed.</p> <p>Conclusions</p> <p>Our package provides users of the Illumina Infinium Methylation assays with a simplified, automated, open-source quality control and primary analysis of their methylation data. Moreover, to enhance its use by experimental researchers, the tool is being distributed along with the scripts necessary for its implementation in the Galaxy workbench. Finally, although it was originally developed for HumanMethylation27, we proved its compatibility with data generated with the HumanMethylation450 Bead Chip.</p

SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data

<p>Abstract</p> <p>Background</p> <p>Censored data are increasingly common in many microarray studies that attempt to relate gene expression to patient survival. Several new methods have been proposed in the last two years. Most of these methods, however, are not available to biomedical researchers, leading to many re-implementations from scratch of ad-hoc, and suboptimal, approaches with survival data.</p> <p>Results</p> <p>We have developed SignS (Signatures for Survival data), an open-source, freely-available, web-based tool and R package for gene selection, building molecular signatures, and prediction with survival data. SignS implements four methods which, according to existing reviews, perform well and, by being of a very different nature, offer complementary approaches. We use parallel computing via MPI, leading to large decreases in user waiting time. Cross-validation is used to asses predictive performance and stability of solutions, the latter an issue of increasing concern given that there are often several solutions with similar predictive performance. Biological interpretation of results is enhanced because genes and signatures in models can be sent to other freely-available on-line tools for examination of PubMed references, GO terms, and KEGG and Reactome pathways of selected genes.</p> <p>Conclusion</p> <p>SignS is the first web-based tool for survival analysis of expression data, and one of the very few with biomedical researchers as target users. SignS is also one of the few bioinformatics web-based applications to extensively use parallelization, including fault tolerance and crash recovery. Because of its combination of methods implemented, usage of parallel computing, code availability, and links to additional data bases, SignS is a unique tool, and will be of immediate relevance to biomedical researchers, biostatisticians and bioinformaticians.</p