The primary mission of the Bioinformatics Shared Resource (BISR) is to support the implementation of bioinformatics resources for cancer research at Dartmouth. Our goal is to provide expert consultation and collaboration for research projects of NCCC members. The Bioinformatics Shared Resource also strives to educate members of the community in different aspects of computational biology by providing regular workshops and seminars.
We provide a wide range of different services including applied bioinformatics and data mining, computer programming and software engineering, database development and programming and high-performance computing and systems administration. We look forward to helping you plan, execute, analyze and interpret your next biomedical research study.
The BISR offers a wide variety of different applied bioinformatics analysis services for genetic, genomic and proteomic studies. This includes use of state of the art software such as the Bioconductor package in R to normalize, transform and analyze your gene expression microarray data using both supervised (e.g. SAM) and unsupervised (cluster analysis) methods. For an example, see the recent paper from Mark Israel's lab that includes a bootstrapped hierarchical cluster analysis of microRNA results (Gaur et al. 2007).
The Cancer Center's Genomics core, with whom we work closely, is an important generator of array and high-throughput sequencing data for the Bioinformatics core.
We also offer a number of advanced machine learning and data mining methods for identifying complex patterns of genetic, genomic, and proteomic biomarkers associated with discrete or continuous biomedical endpoints. For an example, see the recent paper from Angeline Andrew and Margaret Karagas that used data mining methods to identify combinations of genetic and environmental risk factors for bladder cancer (Andrew et al. 2006).
In addition to bioinformatics analysis, the BISR also offers services to assist with the interpretation of 'omics' results. We offer our own Exploratory Visual Analysis (EVA) database and software for exploring analytical results in the context of pathways and Gene Ontology, for example, and we offer access to two different commercial pathway analysis products to assist you with making connections between your results and specific pathways, or to create your own novel pathways. These include Pathway Studio and Ingenuity IPA, each with particular strengths. For an example, see the recent paper by Angeline Andrew that used both of these tools to interpret gene expression microarray results (Andrew et al. 2008). We also have expertise in the use of publicly-accessible web sites for bioinformatics data analysis, including NCBI, Galaxy, UCSC genome browser, and provide access to the powerful and user-friendly commercial bioinformatics package CLC Genomics Workbench.
The BISR offers computer programming support using a wide variety of computer languages and software packages including C, C++, Java, Perl, Python, R, HTML, PHP, Visual Basic, Objective-C, LabView, etc. Most of our programming is carried out on PCs and servers running the Linux operating system, but we also have OSX and IOS expertise as well. As such, we have access to and make use of the Portland Group compilers, debugger, and profiler (pgcc, pgCC, pgf77, pgf90, pgdbg, pgprof), Intel compilers, debugger, and math library (icc, ifort, idb), GNU compilers and debugger (gcc, g77, gdb), Java compiler and debugger (javac, jdb), and the Data Display debugger (ddd). The senior BISR staff have extensive experience with all these computer languages on the major platforms (Linux, Windows, OSX). The BISR also has significant experience designing software and offers this as a service. For an example, see the SCOPE project for identifying regulatory motifs in DNA sequences from the Gross lab.
Database development, programming and administration services are offered using Oracle and mySQL. Comprehensive Oracle support is made possible through a Dartmouth site license. Thus, there are no chargebacks necessary for the Oracle license. The BISR maintains its own database solution called Metatable Database Development System (MDDS) that was specifically designed and implemented in Oracle for integrating research data and clinical data. This system has already been modified and expanded for several projects, including the NCCC billing and financial database for the shared resources. The BISR currently supports and makes available the GeneTraffic microarray database.
CLC Genomics Workbench is a user-friendly, cross-platform bioinformatics analysis tool for sequencing and array data. It is powerful enough to be almost the only tool needed for all types of bioinformatics analysis, including SNP detection, ChIP-seq, RNA-seq, metagenomics, workflow support, de novo assembly, and much more.
Analyses can be run on a local desktop computer, or on a 348 core server, if computational time is an issue.
Dartmouth researchers have access to the CLC Genomics Workbench and Server via a single floating license. Researchers wanting to use CLC Genomics Workbench should contact Walter Taylor for installation instruction and logon information.
Galaxy is a open-source bioinformatics tool created at Pennsylvania State University. Like the commericial alternative CLC Genomics Workbench, it attempts to offer bioinformatics analysis modules for most bioinformatics data analysis needs. Galaxy is web-based, so it is accessible from any web browser. It can be accessed at PSU, but for performance reasons, we have installed a copy on our Dartmouth cluster.
A collection of analytic tools for managing, analyzing, and visualizing multifaceted genomic and phenotypic data. It consists of 4 modules. SNP Analysis, CNV Analysis, DNA-Seq Analysis, and RNA-Seq Analysis, as well as an SVS Viewer. For details, see http://www.goldenhelix.com/SNP_Variation/
* Interpret gene expression and other high throughput data
* Build, expand and analyze pathways
* Find relationships among genes, proteins, cell processes and
* Draw publication-quality pathway diagrams"