Data from: Evidence that hepatitis C virus genome partly controls infection outcome

Hartfield M, Bull R, White PA, Lloyd A, Luciani F, Alizon S

Date Published: November 5, 2013

DOI: http://dx.doi.org/10.5061/dryad.3978f

 

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Title HartfieldetalHCVAnalysis
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Description README.TXT FOR SIMULATION FILES. This file is the source code for the Phylogenetic analysis used in the Hartfield et al. paper "Evidence that HCV genome partly controls infection outcome". Simulations are written in R (http://www.r-project.org/). Files included are: - HeritibilitySim.R: Simulating trait transmission along a tree. - Randomisation.R: Analysis of the true and randomised tipset data to determine estimates of phylogenetic signal. - BT_Rand.sh: Shell script to automate analysis of randomisation tip analysis. - command.txt: File needed to run BayesTraits analysis from shell prompt. - G1HITS_state.txt: Example tipset file (chronic/clearer outcome for genotype 1 data). See blurb at start of each program for description and how to execute. Please also note that R code uses the 'ape' package for R, which needs to be installed prior to execution. The full analysis also uses the BayesTraits package, available from http://www.evolution.rdg.ac.uk/BayesTraits.html. Comments should be sent to Matthew Hartfield (matthew.hartfield@ird.fr).
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When using this data, please cite the original publication:

Hartfield M, Bull R, White PA, Lloyd A, Luciani F, Alizon S (2014) Evidence that hepatitis C virus genome partly controls infection outcome. Evolutionary Applications 7(5): 533–547. http://dx.doi.org/10.1111/eva.12151

Additionally, please cite the Dryad data package:

Hartfield M, Bull R, White PA, Lloyd A, Luciani F, Alizon S (2014) Data from: Evidence that hepatitis C virus genome partly controls infection outcome. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.3978f
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