View source: R/immunogen_mh_tools_2.r
Implementation of the Metropolis-Hastings algorithm to find posterior distributions of pHLA immunogenicity for a single peptide
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eli.dat |
ELISpot dataset |
mol.names |
Names of the HLA molecules in the ELISpot dataset |
init_h |
Initial state of the MH chain, can be produced randomly by generate_random_hypothesis |
max_steps |
The required length of the chain. The default value, 5000, is too low but this was done for debugging reasons. |
pep |
Peptide currently being processed |
unif.prop |
If TRUE, choose proposal states from [0,1]^m |
radius |
If unif.prop is FALSE, we look for a proposal state in a hypercube around h restricted by radius. Should be trained such that the acceptance rate of the chain is around 50%, see example.r. |
p.df |
Dataframe which describes the parameters of the prior distributions for each HLA |
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