Web app helps researchers explore cancer genetics

July 23, 2015 by Kevin Stacey
Web app helps researchers explore cancer genetics

Brown University computer scientists have developed a new interactive tool to help researchers and clinicians explore the genetic underpinnings of cancer.

The tool—dubbed MAGI, for Mutation Annotation and Genome Interpretation—is an open-source web application that enables users to search, visualize, and annotate large public cancer genetics datasets, including data from The Cancer Genome Atlas (TCGA) project.

"The main motivation for MAGI has been to reduce the computational burden required for researchers or doctors to explore and annotate cancer genomics data," said Max Leiserson, a Ph.D. student at Brown who led the development of the tool. "MAGI lets users explore these data in a regular web browser and with no computational expertise required."

In addition to viewing TCGA data, the portal also allows users to upload their own data and compare their findings to those in the larger databases.

"Over the last decade, 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," said Ben Raphael, director of Brown's Center for Computational and Molecular Biology, who helped oversee the project. "At the same time, as sequencing has gotten faster and cheaper, individual researchers have begun sequencing samples from their own studies, sometimes from just a few tumors."

The video will load shortly.

By uploading their data to MAGI, researchers can leverage the large public datasets to help interpret their own data.

"In cancer genomics, there's real value in large sample sizes because mutations are diverse and spread all over the genome," Raphael said. "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 data from TCGA already loaded. 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 other information.

Those same search and visualization capabilities are available for user-uploaded data, which enables researchers to look at their own data side-by-side with TCGA data. Users can also annotate TCGA data, appending new findings, academic papers and other relevant information.

"When someone uploads data to MAGI, they can use the public data to help them interpret their own dataset," Raphael said. "But in the process, they might also be able say something about the public data. We thought: wouldn't it be great if users could record that information and share it?"

The MAGI project started as a means of looking at the output from algorithms that Raphael's lab develops. Those algorithms comb through large genome datasets, helping to pick out the mutations that are important to cancer development and distinguishing them from benign mutations that are just along for the ride.

"As we were developing tools to visualize our own results, we realized that other researchers might also find these tools useful," Raphael said. "We decided to develop a public portal for the cancer genomics research community."

The lab is making MAGI available for free, with the hope that many in the genomics community will take advantage of it.

"We think this could be a really useful piece of software," Raphael said. "There's great value in just being able to look at these data. We hope MAGI will lead to some new discoveries."

Explore further: Algorithm identifies networks of genetic changes across cancers

More information: "MAGI: visualization and collaborative annotation of genomic aberrations." Nature Methods 12, 483–484 (2015) DOI: 10.1038/nmeth.3412

Related Stories

Algorithm identifies networks of genetic changes across cancers

December 15, 2014
The algorithm, called Hotnet2, was used to analyze genetic data from 12 different types of cancer assembled as part of the pan-cancer project of The Cancer Genome Atlas (TCGA). The research looked at somatic mutations—those ...

Computer algorithms help find cancer connections

May 1, 2013
Powerful data-sifting algorithms developed by computer scientists at Brown University are helping to untangle the profoundly complex genetics of cancer. In a study reported today in the New England Journal of Medicine, researchers ...

Cancer Genomics Hub adds childhood cancer data

January 9, 2014
Researchers studying the genetics of childhood cancers now have access to a large and growing set of genomic data through the Cancer Genomics Hub (CGHub) operated by the University of California, Santa Cruz. The data come ...

Oncogenic signatures mapped in TCGA a guide for the development of personalized therapy

September 27, 2013
Clinical trial design for new cancer therapies has historically been focused on the tissue of origin of a tumor, but a paper from researchers at Memorial Sloan-Kettering Cancer Center published on September 26 in Nature Genetics ...

New genomics tool could help predict tumor aggressiveness, treatment outcomes

April 17, 2015
A new method for measuring genetic variability within a tumor might one day help doctors identify patients with aggressive cancers that are more likely to resist therapy, according to a study led by researchers now at The ...

Thyroid cancer genome analysis finds markers of aggressive tumors

October 23, 2014
A new comprehensive analysis of thyroid cancer from The Cancer Genome Atlas Research Network has identified markers of aggressive tumors, which could allow for better targeting of appropriate treatments to individual patients.

Recommended for you

Scientists develop novel 'dot' system to improve cancer detection

August 24, 2017
Researchers at Sanford Burnham Prebys Medical Discovery Institute (SBP) have developed a proof-of-concept nanosystem that dramatically improves the visualization of tumors. Published today in Nature Communications, the platform ...

Study provides insight into link between two rare tumor syndromes

August 22, 2017
UCLA researchers have discovered that timing is everything when it comes to preventing a specific gene mutation in mice from developing rare and fast-growing cancerous tumors, which also affects young children. This mutation ...

Retaining one normal BRCA gene in breast, ovarian cancers influences patient survival

August 22, 2017
Determining which cancer patients are likely to be resistant to initial treatment is a major research effort of oncologists and laboratory scientists. Now, ascertaining who might fall into that category may become a little ...

Study identifies miR122 target sites in liver cancer and links a gene to patient survival

August 22, 2017
A new study of a molecule that regulates liver-cell metabolism and suppresses liver-cancer development shows that the molecule interacts with thousands of genes in liver cells, and that when levels of the molecule go down, ...

Zebrafish larvae could be used as 'avatars' to optimize personalized treatment of cancer

August 21, 2017
Portuguese scientists have for the first time shown that the larvae of a tiny fish could one day become the preferred model for predicting, in advance, the response of human malignant tumors to the various therapeutic drugs ...

Scientists discover vitamin C regulates stem cell function, curbs leukemia development

August 21, 2017
Not much is known about stem cell metabolism, but a new study from the Children's Medical Center Research Institute at UT Southwestern (CRI) has found that stem cells take up unusually high levels of vitamin C, which then ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.