Biology subjects

Goecks, J.

Publications and source records attributed to Goecks, J..

21 records · Page 2Linked to original sources

bioRxiv2017

Practical computational reproducibility in the life sciences

Many areas of research suffer from poor reproducibility. This problem is particularly acute in computationally intensive domains where results rely on a series of complex methodological decisions that are not well captured by traditional publication approaches. Various guidelines have emerged for achieving reproducibility, but practical implementation of these practices remains difficult. This is because reproducing published computational analyses requires installing many software tools plus associated libraries, connecting tools together into the complete pipeline, and specifying parameters. Here we present a suite of recently emerged technologies which make computational reproducibility not just possible, but, finally, practical in both time and effort. By combining a system for building highly portable packages of bioinformatics software, containerization and virtualization technologies for isolating reusable execution environments for these packages, and an integrated workflow system that automatically orchestrates the composition of these packages for entire pipelines, an unprecedented level of computational reproducibility can be achieved.

bioinformatics↗

bioRxiv2017

Enabling Precision Medicine via standard communication of NGS provenance, analysis, and results

A personalized approach based on a patients or pathogens unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to FAIR guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet lab procedures to computational methods. The BioCompute framework (https://osf.io/zm97b/) enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCO) offer that standard, and are freely accessible as a GitHub organization (https://github.com/biocompute-objects) following the \"Open-Stand.org principles for collaborative open standards development\". By communication of high-throughput sequencing studies using a BCO, regulatory agencies (e.g., FDA), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next generation sequencing workflow exchange, reporting, and regulatory reviews.

scientific communication and education↗

bioRxiv2017

Interactive analysis of Long-read RNA isoforms with Iso-Seq Browser

BackgroundLong-read RNA sequencing, such as Pacific Biosciences Iso-Seq method, enables generation of sequencing reads that are 10 kilobases or even longer. These reads are ideal for discovering splice junctions and resolving full-length gene transcripts without time-consuming and error-prone techniques such as transcript assembly and junction inference.\n\nResultsIso-Seq Browser is a Web-based visual analytics tool for long-read RNA sequencing data produced by Pacific Biosciences isoform sequencing (Iso-Seq) techniques. Key features of the Iso-Seq Browser are: 1) an exon-only web-based interface with zooming and exon highlighting for exploring reference gene transcripts and novel gene isoforms, 2) automated grouping of transcripts and isoforms by similarity, 3) many customization features for data exploration and creating publication ready figures, and 4) exporting selected isoforms into fasta files for further analysis. Iso-Seq Browser is written in Python using several scientific libraries. The application and analyses described in this paper are freely available to both academic and commercial users at https://github.com/goeckslab/isoseq-browser\n\nConclusionsIso-Seq Browser enables interactive genome-wide visual analysis of long RNA sequence reads. Through visualization, highlighting, clustering, and filtering of gene isoforms, ISB makes it simple to identify novel isoforms and novel isoform features such as exons, introns and untranslated regions.

bioinformatics↗