Research Computing supports scientific and high-performance computing via the Research Computing Scientific Grid Cluster, as well as via software and applications.
Research Computing Scientific Grid Cluster (RCSGC)
The Research Computing Scientific Grid Cluster is a joint project with Biostatistics and Computational Biology, supported in part by the Claudia Adams Barr Program in Innovative Basic Cancer Research.
Given the demands of modern genomics and proteomics research, the RCSGC was designed to be adaptable and scalable to ensure the DFCI research community has the right tools to support their efforts. A DFCI-only resource, this high-performance compute environment undergoes continuous improvement. To best meet DFCI research community needs, we encourage RCSGC users to partner with us in ensuring the success of the system and working to enhance service and performance.
For more information about the RCSGC environment and for information to include in grants and manuscripts, please contact us.
Software and applications
Qiagen Informatics Workbench
CLC Genomics Workbench
CLC Genomics Workbench is designed to solve the data analysis challenges of high-throughput sequencing with high-throughput sequencing machines.
CLC Genomics Workbench enables researchers to rapidly analyze and visualize large amounts of data generated by NGS machines. Its user-friendly and intuitive interface essentially takes high-throughput analysis solely from bioinformatics programmers doing command-line scripts, and opens it up to scientists searching for biological results.
CLC Genomics Workbench incorporates cutting-edge technology and algorithms, while also supporting and integrating with the rest of a typical NGS workflow. CLC Genomics Workbench supports key next-generation sequencing features within genomics, transcriptomics, and epigenomics, and includes all the tools of CLC Main Workbench.
To learn more, visit the vendor website at www.clcbio.com/products/clc-genomics-workbench.
CLC Biomedical Workbench
CLC Biomedical Workbench offers flexible, ready-to-use analysis workflows. Its main features include the ability to quickly analyze complex data, modify or personalize workflows, filter and visualize your data, and compare results with relevant databases. Built upon the Genomics Workbench framework, this software has been optimized for use with samples from humans or a number of model organisms.
To learn more, visit the vendor website at qiagenbioinformatics.com/products/biomedical-genomics-workbench.
CLC Main Workbench
CLC Main Workbench contains a variety of toolkits to work with DNA, RNA, and protein analysis. These tools include gene expression analysis, primer design, molecular cloning, phylogenetic analyses, and more.
For a comprehensive list of features and capabilities, visit the vendor website at www.clcbio.com/products/clc-main-workbench.
UCSC Genome Browser
UCSC Genome Browser is an interactive website offering access to genome sequence data from a variety of vertebrate and invertebrate species and major model organisms, integrated with a large collection of aligned annotations.
The Browser is a graphical viewer optimized to support fast interactive performance. It is an open-source, web-based tool suite built on top of a MySQL database for rapid visualization, examination, and querying of data at many levels. For more information, please visit rcapps2.dfci.harvard.edu.
Galaxy is a scientific workflow, data integration, and analysis platform that aims to make computational biology accessible to research scientists who do not have computer programming experience. Although it was initially developed for genomics research, it is largely domain agnostic and is now used as a general bioinformatics workflow management system. For more information, please visit rcapps2.dfci.harvard.edu.
GenePatterns is a powerful scientific workflow system that provides access to more than 220 genomic analysis tools. You can use the analysis tools as building blocks to design sophisticated analysis pipelines that capture the methods, parameters, and data used to produce analysis results. Pipelines can be used to create, edit, and share reproducible in silico results. For more information, please visit rcapps2.dfci.harvard.edu.