inferCNVBayesNet {infercnv} | R Documentation |
Uses Markov Chain Monte Carlo (MCMC) and Gibbs sampling to estimate the posterior probability of being in one of six Copy Number Variation states (states: 0, 0.5, 1, 1.5, 2, 3) for CNV's identified by inferCNV's HMM. Posterior probabilities are found for the entire CNV cluster and each individual cell line in the CNV.
inferCNVBayesNet(file_dir, infercnv_obj, HMM_states, out_dir, resume_file_token, model_file = NULL, CORES = 1, postMcmcMethod = NULL, plotingProbs = TRUE, quietly = TRUE, diagnostics = FALSE, HMM_type = HMM_type, k_obs_groups = k_obs_groups, cluster_by_groups = cluster_by_groups, reassignCNVs = TRUE, no_plot = no_plot)
file_dir |
Location of the directory of the inferCNV outputs. |
infercnv_obj |
InferCNV object. |
HMM_states |
InferCNV object with HMM states in expression data. |
out_dir |
(string) Path to where the output file should be saved to. |
resume_file_token |
(string) String token that contains some info on settings used to name files. |
model_file |
Path to the BUGS Model file. |
CORES |
Option to run parallel by specifying the number of cores to be used. (Default: 1) |
postMcmcMethod |
What actions to take after finishing the MCMC. |
plotingProbs |
Option for adding plots of Cell and CNV probabilities. (Default: TRUE) |
quietly |
Option to print descriptions along each step. (Default: TRUE) |
diagnostics |
Option to plot Diagnostic plots and tables. (Default: FALSE) |
HMM_type |
The type of HMM that was ra, either 'i3' or 'i6'. Determines how many state were predicted by the HMM. |
k_obs_groups |
Number of groups in which to break the observations. (default: 1) |
cluster_by_groups |
If observations are defined according to groups (ie. patients), each group of cells will be clustered separately. (default=FALSE, instead will use k_obs_groups setting) |
reassignCNVs |
(boolean) Given the CNV associated probability of belonging to each possible state, reassign the state assignments made by the HMM to the state that has the highest probability. (default: TRUE) |
no_plot |
(boolean) Option set by infercnv::run() for producing visualizations. |
Returns a MCMC_inferCNV_obj and posterior probability of being in one of six Copy Number Variation states (states: 0, 0.5, 1, 1.5, 2, 3) for CNV's identified by inferCNV's HMM.
data(data) data(annots) data(genes) data(HMM_states) infercnv_obj <- infercnv::CreateInfercnvObject(raw_counts_matrix=data, gene_order_file=genes, annotations_file=annots, ref_group_names=c("normal")) out_dir = tempfile() infercnv_obj <- infercnv::run(infercnv_obj, cutoff=1, out_dir=out_dir, cluster_by_groups=TRUE, denoise=TRUE, HMM=TRUE, num_threads=2, no_plot=TRUE) mcmc_obj <- infercnv::inferCNVBayesNet( infercnv_obj = infercnv_obj, HMM_states = HMM_states, file_dir = out_dir, postMcmcMethod = "removeCNV", out_dir = out_dir, resume_file_token = "HMMi6.hmm_mode-samples", quietly = TRUE, CORES = 2, plotingProbs = FALSE, diagnostics = FALSE, HMM_type = 'i6', k_obs_groups = 1, cluster_by_groups = FALSE, reassignCNVs = FALSE, no_plot = TRUE)