Consider the following example: A researcher wants to identify protein-coding exons containing the highest density of SNPs. The goal of Galaxy is to solve these issues. Most experimental biologists cannot fully take advantage of genomic data due to a formidable wall of countless and unnecessary computational issues. Galaxy rapidly has become the most popular choice for integrated next generation sequencing (NGS) analytics and collaboration, where users can perform, document, and share complex analysis within a single interface in an unprecedented number of ways. We will demonstrate through a series of biomedically relevant protocols how Galaxy specifically brings together 1) data retrieval from public and private sources, for example, UCSC’s Eukaryote and Microbial Genome Browsers ( ), 2) custom tools (wrapped Unix functions, format standardization/conversions, interval operations) and 3 rd party analysis tools, for example, Bowtie/Tuxedo Suite ( ), Lastz ( SAMTools ( ), FASTX-toolkit ( / fastx_toolkit), and MACS ( / MACS), and creates results formatted for visualization in tools such as the Galaxy Track Browser (GTB, /wiki/Learn/Visualization), UCSC Genome Browser ( ), Ensembl ( and GeneTrack ( genetrack.bx.psu.edu). The authors believe that Galaxy ( ) provides a powerful solution that simplifies data acquisition and analysis in an intuitive web-application, granting all researchers access to key informatics tools previously only available to computational specialists working in Unix-based environments. As creating and obtaining data has become easier, the key decision faced by many researchers is a practical one: where and how should an analysis be performed? Datasets are large and analysis tool set-up and use is riddled with complexities outside of the scope of core research activities. Innovations in biomedical research technologies continue to provide experimental biologists with novel and increasingly large genomic and high-throughput data resources to be analyzed.
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