Scrolling Headlines:

Small-ball lineup sparks UMass men’s basketball comeback over Saint Joseph’s -

January 14, 2018

UMass men’s basketball tops St. Joe’s in wild comeback -

January 14, 2018

UMass women’s track and field have record day at Beantown Challenge -

January 14, 2018

UMass women’s basketball blows halftime lead to Saint Joseph’s, fall to the Hawks 84-79. -

January 14, 2018

UMass hockey beats Vermont 6-3 in courageous win -

January 13, 2018

Makar, Leonard score but UMass can only muster 2-2 tie with Vermont -

January 13, 2018

Pipkins breaks UMass single game scoring record in comeback win over La Salle -

January 10, 2018

Conservative student activism group sues UMass over free speech policy -

January 10, 2018

Report: Makar declines invite from Team Canada Olympic team -

January 10, 2018

Prince Hall flood over winter break -

January 10, 2018

Minutemen look to avoid three straight losses with pair against Vermont -

January 10, 2018

Men’s and women’s track and field open seasons at Dartmouth Relays -

January 10, 2018

Turnovers and poor shooting hurt UMass women’s basketball in another conference loss at St. Bonaventure -

January 8, 2018

Shorthanded, UMass men’s basketball shocks Dayton with 62-60 win -

January 7, 2018

Northampton City Council elects Ryan O’Donnell as new council president -

January 7, 2018

UMass power play stays hot but Minutemen lose 8-3 to UMass Lowell -

January 7, 2018

UMass hockey falls to UMass Lowell in 8-3 blowout -

January 7, 2018

UMass hockey falls short against Yale in 5-3 loss Friday -

January 5, 2018

Otis Livingston II, George Mason drop UMass men’s basketball 80-72 -

January 3, 2018

Johnston: UMass fails to earn first conference win against George Mason -

January 3, 2018

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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