Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

The Marker State Space (MSS) Method for Classifying Clinical Samples

Fallon, BP and Curnutte, B and Maupin, KA and Partyka, K and Choi, S and Brand, RE and Langmead, CJ and Tembe, W and Haab, BB (2013) The Marker State Space (MSS) Method for Classifying Clinical Samples. PLoS ONE, 8 (6).

Published Version
Available under License : See the attached license file.

Download (1MB) | Preview
[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications. © 2013 Fallon et al.


Social Networking:
Share |


Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Fallon, BP
Curnutte, B
Maupin, KA
Partyka, K
Choi, S
Brand, REreb53@pitt.eduREB53
Langmead, CJ
Tembe, W
Haab, BB
ContributionContributors NameEmailPitt UsernameORCID
Date: 4 June 2013
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 8
Number: 6
DOI or Unique Handle: 10.1371/journal.pone.0065905
Schools and Programs: School of Medicine > Medicine
Refereed: Yes
Date Deposited: 15 Jul 2013 20:10
Last Modified: 02 Feb 2019 17:55


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item