One_step_clustering: Cellularity clustering

In DeveauP/QuantumClone: Clustering Mutations using High Throughput Sequencing (HTS) Data

Description

Wrap up function that clusters cellularities. This is based on the most likely possibility for each mutation, give ints frequency and genotype.

Usage

One_step_clustering(
  SNV_list,
  FREEC_list = NULL,
  contamination,
  nclone_range = 2:5,
  clone_priors = NULL,
  prior_weight = NULL,
  Initializations = 1,
  preclustering = "FLASH",
  simulated = FALSE,
  epsilon = NULL,
  save_plot = TRUE,
  ncores = 1,
  restrict.to.AB = FALSE,
  output_directory = NULL,
  model.selection = "BIC",
  optim = "default",
  keep.all.models = FALSE,
  force.single.copy = FALSE
)

Arguments

SNV_list	A list of dataframes (one for each sample), with as columns : (for the first column of the first sample the name of the sample), the chromosome "Chr",the position of the mutation "Start", the number of reads supporting variant "Alt", as well as the total number of reads overlapping position "Depth", and if the output from FREEC for the samples are not associated, the genotype "Genotype".
FREEC_list	list of dataframes from FREEC for each samples (usually named Sample_ratio.txt), in the same order as SNV_list
contamination	Numeric vector describind the contamination in all samples (ranging from 0 to 1). Default is 0. No longer used for clustering.
nclone_range	A number or range of clusters that should be used for clustering
clone_priors	List of vectors with the putated position of clones
prior_weight	Numeric with the proportion mutations in each clone
Initializations	Number of initial conditions to be tested for the EM algorithm
preclustering	The type of preclustering used for priors: "Flash","kmedoid" or NULL. NULL will generate centers using uniform distribution. WARNING: overrides priors given
simulated	Should be TRUE if the data has been been generated by the QuantumCat algorithm
epsilon	Stop value: maximal admitted value of the difference in cluster position and weights between two optimization steps. If NULL, will take 1/(average depth)
save_plot	Should the plots be saved? Default is TRUE
ncores	Number of cores to be used during EM algorithm
restrict.to.AB	Boolean: Should the analysis keep only sites located in A and AB sites in all samples?
output_directory	Directory in which to save results
model.selection	The function to minimize for the model selection: can be "AIC", "BIC", or numeric. In numeric, the function uses a variant of the BIC by multiplication of the k*ln(n) factor. If >1, it will select models with lower complexity.
optim	use L-BFS-G optimization from R ("default"), or from optimx ("optimx"), or Differential Evolution ("DEoptim")
keep.all.models	Should the function output the best model (default; FALSE), or all models tested (if set to true)
force.single.copy	Should all mutations in overdiploid regions set to single copy? Default is FALSE

Value

list of lists

Top level

List of all possibilities

dataframe

Table of hierarchical relations

numeric

probability of this tree

Examples

Mutations<-QuantumClone::Input_Example
 for(i in 1:2){
 Mutations[[i]]<-cbind(rep(paste("Example_",i,sep=""),times=10),Mutations[[i]])
 colnames(Mutations[[i]])[1]<-"Sample"
}
print("The data should look like this:")
print(head(Mutations[[1]]))

cat("Cluster data: will try to cluster between 3 and 4 clones, with 1 maximum search each time,
      and will use priors from preclustering (e.g. k-medoids on A and AB sites)")
print("The genotype is provided in the list frame, and
          there is no associated data from FREEC to get genotype from.")
print("The computation will run on a single CPU.")
Clustering_output<-One_step_clustering(SNV_list = Mutations,
FREEC_list = NULL,contamination = c(0,0),nclone_range = 3:4,
clone_priors = NULL,prior_weight = NULL ,
Initializations = 1,preclustering = "FLASH", simulated = TRUE,
save_plot = FALSE,ncores=1,output_directory=NULL)
print("The data can be accessed by Clustering_output$filtered_data")
print("All plots are now saved in the working directory")

DeveauP/QuantumClone documentation built on Oct. 29, 2021, 8:56 a.m.