An interactive tool, called 'Mutation Annotation and Genome Interpretation' (MAGI), that can help researchers and clinicians explore the genetic underpinnings of cancer has been developed by scientists. The tool is an open-source web application that enables users to search, visualize, and annotate large public cancer genetic datasets, including data from The Cancer Genome Atlas (TCGA) project. Besides, it also allows users to upload their own data and compare their results to those in the larger databases.
Max Leiserson, lead developer of the tool, said, "MAGI lets users explore these data in a regular web browser and with no computational expertise required."
Over the last 10 years, researchers working with TCGA have sequenced genes from thousands of tumors and dozens of cancer types in an effort to understand which mutations contribute to the development of cancer. At the same time, as sequencing has gotten faster and cheaper, individual scientists have begun sequencing samples from their own studies, sometimes from just a few tumors. By uploading their data to MAGI, the researchers can leverage the large public database to help interpret their own data.
Ben Raphael, director of Brown's Center for Computational and Molecular Biology, said, "In cancer genomes, there's real value in large sample sizes because mutations are diverse and spread all over the genome. If I had just sequenced a few cancer genomes from my local tumor bank, one of the first things I'd want to do is compare my data to these big public datasets and look for similarities."
MAGI has already loaded data from TCGA, and users can search by cancer type, by individual genes, or by groups of genes. The output offers several ways of visualizing the search results, showing how often a given gene is mutated across samples, what types of mutations they were, and such other information. Raphael said, "When someone uploads data to MAGI, they can use the public data to help them interpret their own dataset."
The laboratory is making MAGI available for free, with the hope that many in the cancer genomics community will take advantage of it.