Great appriciation for researchers.
Today, the technology is improved so much that we have an app for almost everything like the apps for news, social networking, banking, entertainment and so on. Now the news is that, the scientists of Brown University have built an app called MAGI (Mutation Annotation and Genome Interpretation) using which the users can compare their results with several cancer genetic datasets.
Basically, ‘MAGI’ is an interactive and open source application which allows clinicians and researchers to investigate the traces of cancer. Using this tool, the users can search, visualise and also interpret public cancer genetic datasets including the data from TCGA (The Cancer Genome Atlas) project. Along with TGCA data, the app also allows you to upload your own data and compare the results with those in the database.
Why ‘MAGI’ is developed?
According to Max Leiserson, the lead developer of MAGI, the app enables users to explore cancer genomics data using a regular web browser even if he/she doesn’t have any computational expertise. He also says that computational burden on the doctors and researchers, has been the main reason for the development of such an amazing application.
Over the past ten years, lots of researchers working on TCGA had sequenced the genes from about thousands of tumours and cancer types to understand the mutations that contribute to the development of cancer. This effort behind the analysis motivated the scientists of Brown University which led to the development of MAGI.
How useful the app has been?
The app has really been useful for clinicians and laboratory researchers. Today, the gene sequencing has become faster and cheaper as well; the researchers have actually started sequencing the samples based on their own studies and sometimes with reference to just a few tumours. But now, they can upload the results to MAGI and they can make use of the huge public datasets to interpret their own data.
According to Ben Raphael, the Director of Brown University, mutations are diverse and they are spread all over the genome. So in cancer genomes, the real value lies in large sample sizes. He also explains that, if he had sequenced a few cancer genomes from a local tumour bank, the first thing he would do is to compare his data with the huge public datasets for similarities. The output generated by MAGI offers several ways to visualize the results. It also shows how often a gene is mutated across the samples and other information.
As already told above, today the gene sequencing has become faster so that the lab technicians and researchers can use the genomic data to diagnose and also to develop a course of treatment for variety of cancers. The lab is intended to make the app available freely so that those who are in cancer genomics community can make use of it.
