View source: R/BN_module_func.R
| second_adapt_phase | R Documentation |
second_adapt_phase This phase identifies the proposal distribution
that has a similar covariance structure with the target distribution.
second_adapt_phase( transient.phase_net, omics, layers_def, B_prior_mat, energy_all_configs_node, prob_mbr, BGe_score_all_configs_node, parent_set_combinations, annot, woPKGE_belief = 0.5 )
transient.phase_net |
list output of the transient.phase function. |
omics |
named list containing the gene expression (possibly copy number variation and methylation data). Each component of the list is a matrix with samples in rows and features in columns. |
layers_def |
data.frame containing the modality ID, corresponding layer in BN and maximal number of parents from given layer to GE nodes. |
B_prior_mat |
a biological prior matrix. |
energy_all_configs_node |
list of nodes energy for all possible parent set configurations. |
prob_mbr |
numeric vector probability of the MBR step. |
BGe_score_all_configs_node |
list of nodes BGe score for all possible parent set configurations. |
parent_set_combinations |
list of all possible parent set configuration for all nodes available. |
annot |
named list containing the associated methylation probes of given gene. |
woPKGE_belief |
numeric vector to define the belief concerning GE-GE interactions without prior knowledge (default=0.5). |
List of 1 element: first adaption phase + transient phase + second adaption phase result
data(list=c("PK", "TFtarg_mat", "annot", "layers_def", "omics"),
package="IntOMICS")
OMICS_mod_res <- OMICS_module(omics = omics, PK = PK, annot = annot,
layers_def = layers_def, lm_METH = TRUE,
TFtargs = TFtarg_mat, r_squared_thres = 0.3)
first.adapt.phase_net <- first_adapt_phase(omics = OMICS_mod_res$omics,
B_prior_mat = OMICS_mod_res$B_prior_mat,
energy_all_configs_node =
OMICS_mod_res$pf_UB_BGe_pre$energy_all_configs_node,
len = 5, prob_mbr = 0.07, annot = OMICS_mod_res$annot,
layers_def = OMICS_mod_res$layers_def,
BGe_score_all_configs_node = OMICS_mod_res$pf_UB_BGe_pre$BGe_score_all_configs_node,
parent_set_combinations = OMICS_mod_res$pf_UB_BGe_pre$parents_set_combinations)
transient.phase_net <- transient_phase(prob_mbr = 0.07,
first.adapt.phase_net = first.adapt.phase_net,
omics = OMICS_mod_res$omics, B_prior_mat = OMICS_mod_res$B_prior_mat,
layers_def = OMICS_mod_res$layers_def, annot = OMICS_mod_res$annot,
energy_all_configs_node =
OMICS_mod_res$pf_UB_BGe_pre$energy_all_configs_node,
BGe_score_all_configs_node = OMICS_mod_res$pf_UB_BGe_pre$BGe_score_all_configs_node,
parent_set_combinations = OMICS_mod_res$pf_UB_BGe_pre$parents_set_combinations)
second_adapt_phase(transient.phase_net = transient.phase_net,
omics = OMICS_mod_res$omics, B_prior_mat = OMICS_mod_res$B_prior_mat,
layers_def = OMICS_mod_res$layers_def, woPKGE_belief = 0.5,
energy_all_configs_node =
OMICS_mod_res$pf_UB_BGe_pre$energy_all_configs_node,
prob_mbr = 0.07, annot = OMICS_mod_res$annot,
BGe_score_all_configs_node = OMICS_mod_res$pf_UB_BGe_pre$BGe_score_all_configs_node,
parent_set_combinations =
OMICS_mod_res$pf_UB_BGe_pre$parents_set_combinations)
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