Bio-Docklets: virtualization containers for single-step execution of NGS pipelines

Processing of next-generation sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized postanalysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers toward seamless deployment of preconfigured bioinformatics software and pipelines on any computational platform. We present an approach for abstracting the complex data operations of multistep, bioinformatics pipelines for NGS data analysis. As examples, we have deployed 2 pipelines for RNA sequencing and chromatin immunoprecipitation sequencing, preconfigured within Docker virtualization containers we call Bio-Docklets. Each Bio-Docklet exposes a single data input and output endpoint and from a user perspective, running the pipelines as simply as running a single bioinformatics tool. This is achieved using a “meta-script” that automatically starts the Bio-Docklets and controls the pipeline execution through the BioBlend software library and the Galaxy Application Programming Interface. The pipeline output is postprocessed by integration with the Visual Omics Explorer framework, providing interactive data visualizations that users can access through a web browser. Our goal is to enable easy access to NGS data analysis pipelines for nonbioinformatics experts on any computing environment, whether a laboratory workstation, university computer cluster, or a cloud service provider. Beyond end users, the Bio-Docklets also enables developers to programmatically deploy and run a large number of pipeline instances for concurrent analysis of multiple datasets

MSG-Fast: Metagenomic shotgun data fast annotation using microbial gene catalogs

Background: Current methods used for annotating metagenomics shotgun sequencing (MGS) data rely on a computationally intensive and low-stringency approach of mapping each read to a generic database of proteins or reference microbial genomes. Results: We developed MGS-Fast, an analysis approach for shotgun whole-genome metagenomic data utilizing Bowtie2 DNA-DNA alignment of reads that is an alternative to using the integrated catalog of reference genes database of well-annotated genes compiled from human microbiome data. This method is rapid and provides high-stringency matches (\u3e90% DNA sequence identity) of the metagenomics reads to genes with annotated functions. We demonstrate the use of this method with data from a study of liver disease and synthetic reads, and Human Microbiome Project shotgun data, to detect differentially abundant Kyoto Encyclopedia of Genes and Genomes gene functions in these experiments. This rapid annotation method is freely available as a Galaxy workflow within a Docker image. Conclusions: MGS-Fast can confidently transfer functional annotations from gene databases to metagenomic reads, with speed and accuracy

The management of entrepreneurial social responsibility in the industrial enterprises of Santa Cruz de la Sierra en Bolivia

El trabajo presenta los resultados de un estudio realizado con el fin de valorar la gestión de la responsabilidad social en las empresas industriales de la Ciudad de Santa Cruz de la Sierra en Bolivia. La investigación utiliza varios métodos y técnicas científicos, entre ellos, el cuestionario a través de encuesta, el análisis de contenido y la triangulación de fuentes, los cuales se aplicaron a una muestra estadística representativa del total de empresas cruceñas. Los resultados evidencian que la gestión de la responsabilidad social empresarial es muy débil y que la atención a la dimensión económica sobresale por encima de las dimensiones social y ambiental.This article presents the results of a study carried out with the aim of assessing the management of social responsibility in the industrial enterprises of the City of Santa Cruz de la Sierra in Bolivia. The research uses several scientific methods and techniques, including questionnaires through surveys, content analysis and source triangulation, which were applied to a representative statistical sample of the total number of Santa Cruz enterprises. The results show that the entrepreneurial social responsibility management is very weak and that attention is drawn to the economic dimension over the social and environmental dimensions.Instituto de Investigaciones y Estudios Contable