By NewsGram Staff Writer
Researchers and clinicians exploring the genetic underpinnings of cancer now have a new interactive tool at their disposal to further their study.
The tool – Mutation Annotation and Genome Interpretation (MAGI) – is an open-source web application that enables users to search, visualise, and annotate large public cancer genetic datasets, including data from The Cancer Genome Atlas (TCGA) project.
“MAGI lets users explore these data in a regular web browser and with no computational expertise required,” said Max Leiserson, lead developer of the tool.
The tool also allows users to upload their own data and compare their results to those in the larger, apart from viewing TCGA.
Researchers working with TCGA have sequenced genes from thousands of tumours and dozens of cancer types in an effort to understand which mutations contribute to the development of cancer over the past decade.
Meanwhile, as sequencing has got faster and cheaper, individual researchers have begun sequencing samples from their own studies, sometimes from just a few tumours.
Researchers can leverage the large public data-sets to help interpret their own data by uploading their data to MAGI.
Ben Raphael, director of Brown’s Centre for Computational and Molecular Biology says, “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 tumour bank, one of the first things I’d want to do is compare my data to these big public datasets and look for similarities,” Raphael said.
Users can search MAGI by cancer type, by individual genes, or by groups of genes the data which it has loaded from TCGA.
There are several ways of visualizing the search results, showing how often a given gene is mutated across samples, what types of mutations they were, and other information.
“When someone uploads data to MAGI, they can use the public data to help them interpret their own dataset,” Raphael said.
The MAGI app is available for free, with the hope that many in the cancer genomics community will take advantage of it.
(With inputs from IANS)