Novel classification for global gene signature model for predicting severity of systemic sclerosis

Zariel I Johnson, Jacqueline D Jones, Angana Mukherjee, Dianxu Ren, Carol Feghali-Bostwick, Yvette P Conley and Cecelia C Yates

PLOS ONE, 2018, vol. 13, issue 6, 1-16

Abstract: Progression of systemic scleroderma (SSc), a chronic connective tissue disease that causes a fibrotic phenotype, is highly heterogeneous amongst patients and difficult to accurately diagnose. To meet this clinical need, we developed a novel three-layer classification model, which analyses gene expression profiles from SSc skin biopsies to diagnose SSc severity. Two SSc skin biopsy microarray datasets were obtained from Gene Expression Omnibus. The skin scores obtained from the original papers were used to further categorize the data into subgroups of low (

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0199314

DOI: 10.1371/journal.pone.0199314

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