| Type: | Package |
| Title: | Subclone Multiplicity Allocation and Somatic Heterogeneity |
| Version: | 1.0.0 |
| Date: | 2025-02-07 |
| Description: | Cluster user-supplied somatic read counts with corresponding allele-specific copy number and tumor purity to infer feasible underlying intra-tumor heterogeneity in terms of number of subclones, multiplicity, and allocation (Little et al. (2019) <doi:10.1186/s13073-019-0643-9>). |
| License: | GPL (≥ 3) |
| Imports: | Rcpp, stats, smarter, reshape2, ggplot2 |
| LinkingTo: | Rcpp, RcppArmadillo |
| Encoding: | UTF-8 |
| LazyData: | true |
| Depends: | R (≥ 2.10) |
| RoxygenNote: | 7.2.3 |
| Suggests: | knitr, devtools |
| VignetteBuilder: | knitr |
| NeedsCompilation: | yes |
| Packaged: | 2025-02-26 05:10:10 UTC; Admin |
| Author: | Paul Little [aut, cre] |
| Maintainer: | Paul Little <pllittle321@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-02-27 16:40:06 UTC |
ITH_optim
Description
Performs EM algorithm for a given configuration matrix
Usage
ITH_optim( my_data, my_purity, init_eS, pi_eps0 = NULL, my_unc_q = NULL, max_iter = 4000, my_epsilon = 1e-06)Arguments
my_data | A R dataframe containing the following columns:
|
my_purity | A single numeric value of known/estimated purity |
init_eS | A subclone configuration matrix pre-defined in R list |
pi_eps0 | A user-specified parameter denoting the proportion of loci not explained by the combinations of purity, copy number, multiplicity, and allocation. If |
my_unc_q | An optimal initial vector for the unconstrained |
max_iter | Positive integer, preferably 1000 or more, setting the maximum number of iterations |
my_epsilon | Convergence criterion threshold for changes in the log likelihood, preferably 1e-6 or smaller |
Value
If the EM algorithm converges, the output will be a list containing
iternumber of iterations
convergeconvergence status
unc_q0initial unconstrained subclone proportions parameter
unc_qunconstrained estimate of
qqestimated subclone proportions among cancer cells
CN_MA_piestimated mixture probabilities of multiplicities and allocations given copy number states
etaestimated subclone proportion among tumor cells
purityuser-inputted tumor purity
entropyestimated entropy
inferA R dataframe containing inferred variant allocations (
infer_A), multiplicities (infer_M), cellular prevalences (infer_CP).msmodel size, number of parameters within parameter space
LLThe observed log likelihood evaluated at maximum likelihood estimates.
AIC = 2 * LL - 2 * msNegative AIC, used for model selection
BIC = 2 * LL - ms * log(LOCI)Negative BIC, used for model selection
LOCIThe number of inputted somatic variants.
A collection of pre-defined subclone configurations.
Description
A R list containing subclone configurations in matrix form for 1 to 5 subclones. For each matrix, each column corresponds to a subclone and each row corresponds to a variant's allocation across all subclones. For example, the first row of each matrix is a vector of 1's to represent clonal variants, variants present in all subclones.
Usage
eSFormat
An object of classlist of length 5.
gen_ITH_RD
Description
Simulates observed alternate and reference read counts
Usage
gen_ITH_RD(DATA, RD)Arguments
DATA | The output data.frame from |
RD | A positive integer for the mean read depth generated from the negative binomial distribution |
Value
A matrix of simulated alternate and reference read counts.
gen_subj_truth
Description
Simulates copy number states, multiplicities, allocations
Usage
gen_subj_truth(mat_eS, maxLOCI, nCN = NULL)Arguments
mat_eS | A subclone configuration matrix pre-defined in R list |
maxLOCI | A positive integer number of simulated somatic variant calls |
nCN | A positive integer for the number of allelic copy number pairings to sample from. If |
Value
A list containing the following components:
subj_truthdataframe of each variant's simulated minor (
CN_1) and major (CN_2) copy number states, total copy number (tCN), subclone allocation (true_A), multiplicity (true_M), mutant allele frequency (true_MAF), and cellular prevalence (true_CP)puritytumor purity
etathe product of tumor purity and subclone proportions
qvector of subclone proportions
grid_ITH_optim
Description
This function performs a grid search over enumerated configurations within the pre-defined listeS
Usage
grid_ITH_optim( my_data, my_purity, list_eS, pi_eps0 = NULL, trials = 20, max_iter = 4000, my_epsilon = 1e-06)Arguments
my_data | A R dataframe containing the following columns:
|
my_purity | A single numeric value of known/estimated purity |
list_eS | A nested list of subclone configuration matrices |
pi_eps0 | A user-specified parameter denoting the proportion of loci not explained by the combinations of purity, copy number, multiplicity, and allocation. If |
trials | Positive integer, number of random initializations of subclone proportions |
max_iter | Positive integer, preferably 1000 or more, setting the maximum number of iterations |
my_epsilon | Convergence criterion threshold for changes in the log likelihood, preferably 1e-6 or smaller |
Value
A R list containing two objects.GRID is a dataframe where each row denotes a feasible subclone configuration with corresponding subclone proportion estimatesq and somatic variant allocationsalloc.INFER is a list whereINFER[[i]] corresponds to thei-th row or model ofGRID.
vis_GRID
Description
A simple visualization of SMASH's grid of solutions
Usage
vis_GRID(GRID)Arguments
GRID | The |
Value
A ggplot object for data visualization