Abstract
We present GobyWeb, a web-based system that facilitates the management and analysis of high-throughput sequencing (HTS) projects. The software provides integrated support for a broad set of HTS analyses and offers a simple plugin extension mechanism. Analyses currently supported include quantification of gene expression for messenger and small RNA sequencing, estimation of DNA methylation (i.e., reduced bisulfite sequencing and whole genome methyl-seq), or the detection of pathogens in sequenced data. In contrast to previous analysis pipelines developed for analysis of HTS data, GobyWeb requires significantly less storage space, runs analyses efficiently on a parallel grid, scales gracefully to process tens or hundreds of multi-gigabyte samples, yet can be used effectively by researchers who are comfortable using a web browser. We conducted performance evaluations of the software and found it to either outperform or have similar performance to analysis programs developed for specialized analyses of HTS data. We found that most biologists who took a one-hour GobyWeb training session were readily able to analyze RNA-Seq data with state of the art analysis tools. GobyWeb can be obtained at http://gobyweb.campagnelab.org and is freely available for non-commercial use. GobyWeb plugins are distributed in source code and licensed under the open source LGPL3 license to facilitate code inspection, reuse and independent extensions http://github.com/CampagneLaboratory/gobyweb2-plugins.
Highlights
High-Throughput sequencing (HTS) instruments have been used to develop a variety of cost-effective assays
GobyWeb tags are listed in this manuscript following a description of an analysis and can be used to locate analyses in the GobyWeb demonstration system
We describe the options offered by these menus and data flows in File S1 description and Figures S1, S2, S3, as well as in video tutorials online
Summary
High-Throughput sequencing (HTS) instruments have been used to develop a variety of cost-effective assays. It is not uncommon to generate about three billion 100 base pair long sequence reads per week with one HiSeq 2000 instrument (many core facilities have several similar instruments). Such throughput makes it possible to multiplex assays, which has contributed to reducing the cost of assaying each single sample. The management and analysis of large datasets produced with HTS assays have become a significant challenge for most research groups. HTS data analysis is recognized as a bottleneck of most research studies
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