Hepatitis C Virus Transmission Clusters in Public Health and Correctional Settings, Wisconsin, USA, 2016–20171
Karli R. Hochstatter
2 , Damien C. Tully
2, Karen A. Power, Ruth Koepke, Wajiha Z. Akhtar, Audrey F. Prieve, Thomas Whyte, David J. Bean, David W. Seal, Todd M. Allen
3, and Ryan P. Westergaard
3
Author affiliations: University, New York, New York, USA (K.R. Hochstatter); University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA (K.R. Hochstatter, R. Koepke, W.Z. Akhtar, R.P. Westergaard); London School of Hygiene and Tropical Medicine, London, UK (D.C. Tully); Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA (D.C. Tully, K.A. Power, D.J. Bean, T.M. Allen); Wisconsin Department of Health Services, Madison (R. Koepke, R.P. Westergaard); Wisconsin State Laboratory of Hygiene, Madison (A.F. Prieve, T. Whyte); Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA (D.W. Seal)
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Figure 4
Figure 4. Intrahost genetic variation of representative transmission clusters of hepatitis C virus (HCV) among persons in public health and corrections settings, Wisconsin, USA, 2016–2017, highlighting the genetic relatedness of distinct variants. K-step network contains all possible minimum spanning trees and enables efficient visualization of genetic relatedness among all intrahost hypervariable region 1 (HVR1) variants for persons 84 and 86 (A) and persons 281 and 367 (B). Each node represents an HCV sequence. Color of the node corresponds to the sample of origin: green, found only in the first sample; blue, found only in the second sample. The node size is based on frequency of the HVR1 variant, and edge length is proportional to the modified Hamming distance (does not count positions with insertions or deletions as differences).
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