Scrolling Headlines:

: Nineteen turnovers sink UMass men’s basketball in loss to Fordham Saturday -

January 21, 2017

UMass men’s basketball falls to Fordham behind strong defensive effort by the Rams -

January 21, 2017

UMass hockey can’t take advantage of strong start in 6-1 loss to Boston College -

January 21, 2017

High-powered Eagles soar past UMass -

January 21, 2017

UMass women’s basketball suffers disappointing loss to St. Bonaventure at Mullins Center Thursday -

January 19, 2017

REPORT: Tom Masella out as defensive coordinator for UMass football -

January 19, 2017

Zach Lewis, bench carry UMass men’s basketball in win over St. Joe’s -

January 19, 2017

UMass women’s basketball handles Duquesne at home -

January 16, 2017

UMass men’s basketball’s late comeback falls short after blowing 15-point first-half lead -

January 15, 2017

UMass hockey outlasted at home against No. 6 UMass Lowell -

January 14, 2017

Hailey Leidel hits second buzzer beater of the season to give UMass women’s basketball win over Davidson -

January 13, 2017

UMass football hosts Maine at Fenway Park in 2017 -

January 12, 2017

UMass men’s basketball snaps losing streak and upsets Dayton Wednesday night at Mullins Center -

January 11, 2017

UMass women’s track and field takes second at Dartmouth Relays -

January 10, 2017

UMass hockey falls to No. 5 Boston University at Frozen Fenway -

January 8, 2017

UMass professor to make third appearance on ‘Jeopardy!’ -

January 8, 2017

UMass women’s basketball suffers brutal loss on road against Saint Joseph’s -

January 7, 2017

UMass men’s basketball drops thirds straight, falls to VCU 81-64 -

January 7, 2017

UMass men’s basketball drops tightly-contested conference matchup against George Mason Wednesday night -

January 4, 2017

Late-game defense preserves UMass women’s basketball’s win against rival Rhode Island -

January 4, 2017

UMass study reveals genetic links with disease

Chris Roy/Collegian

A new approach to data analysis has led University of Massachusetts biostatisticians to discover new genetic information linked to common diseases such as diabetes and heart disease, according to a UMass press release.

The team of researchers, led by Andrea Foulkes, has applied this new approach to data analysis to pre-existing databases, revealing the genetic information behind that which causes conditions such as high cholesterol and heart diseases, according to the release.

Foulkes directs the Institute for Computational Biology, Biostatistics and Bioinformatics at UMass. Other members of her team include Rongheng Lin, an assistant professor, and Gregory Matthews and Ujjwall Das, who are both postdoctoral researchers. The work done by the team was supported by the National Institutes of Health National Heart, Lung and Blood Institute, the release stated.

“This new approach to data analysis provides opportunities for developing new treatments. It also advances approaches to identifying people at greatest risk for heart disease,” said Foulkes in the release.

The new style of analysis coined “MixMAP,” which was developed by Foulkes and cardiologist Dr. Muredach Reilly at the University of Pennsylvania, stands for “Mixed modeling of Meta-Analysis P-values,” according to the release. Since this method of statistical analysis is based on pre-existing public information, it “represents a low-cost tool” for researchers, according to the release.

“Another important point is that our method is straightforward to use with freely available computer software and can be applied broadly to advance genetic knowledge of many diseases,” Foulkes added in the release.

Foulkes explained that the new method takes the entire human genome into account and can be generalized to figure out many different diseases. Though the other more widely-used methods of gene tracking and analysis look for a “needle in a haystack,” so to speak, as a disease signal, according to the release, Foulkes’ new method makes use of genome knowledge in DNA regions that “contain several genetic signals for disease variation clumped together. … Thus, it is able to detect groups of unusual variants.”

According to the release, Foulkes characterizes the “MixMAP” technique as a discovery method still in need of scientific validation, although it “goes farther than usual by using sophisticated modeling approaches to quantify error.”

“We’ve done better than simply identify the strongest signals, we’ve quantified measures of association to show they are statistically meaningful,” noted Foulkes in the release.

George Felder can be reached at gfelder@student.umass.edu

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