Description Usage Arguments Value Functions
View source: R/oneThetaModel.R
Fit the maximum likelihood estimate of the parameters for a specific EVE model
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | fitSharedBeta(sharedBeta, tree, gene.data,
colSpecies = colnames(gene.data), extra.var = NULL,
lowerBound = c(theta = -99, sigma2 = 1e-04, alpha = 0.001),
upperBound = c(theta = 99, sigma2 = 9999, alpha = 999),
logTransPars = c("alpha", "sigma2", "beta"), cores = 1, fork = F)
fitOneTheta(tree, gene.data, colSpecies = colnames(gene.data),
extra.var = NULL, lowerBound = c(theta = -99, sigma2 = 1e-04, alpha =
0.001, beta = 0.001), upperBound = c(theta = 99, sigma2 = 9999, alpha =
999, beta = 99), logTransPars = c("alpha", "sigma2", "beta"),
cores = 1, fork = F)
fitTwoTheta(tree, gene.data, isTheta2edge,
colSpecies = colnames(gene.data), extra.var = NULL,
lowerBound = c(theta1 = -99, theta2 = -99, sigma2 = 1e-04, alpha =
0.001, beta = 0.001), upperBound = c(theta1 = 99, theta2 = 99, sigma2 =
9999, alpha = 999, beta = 99), logTransPars = c("alpha", "sigma2",
"beta"), cores = 1, fork = F)
|
sharedBeta |
the shared beta parameter |
tree |
Phylogeny |
gene.data |
A matrix of expression values with samples in columns and genes in rows |
colSpecies |
A character vector with same length as columns in returned expression matrix, specifying the species, i.e. tip labels in the phylogeny, for the corresponding column. |
extra.var |
An optional matrix of technical variance for each expression value. Same dimensions as gene.data (default=NULL) |
lowerBound |
A named numeric vector of the lower bound for the estimated parameters |
upperBound |
A named numeric vector of the upper bound for the estimated parameters |
logTransPars |
A character vector with the names of the parameters that will be log transformed |
cores |
Number of parallel processes to run |
fork |
Use forking for parallel execution |
isTheta2edge |
Logical vector with same length as number of edges in tree specifying whether the corresponding edge theta parameter should be theta2 (TRUE) or theta1 (FALSE) |
A list with:
A matrix with the parameter estimates
The log likelihood for each estimate
Number of iterations of the optimisation routine before reaching the estimate
Error code from the optim
function. 0 means convergence.
Error message from the optim
function.
fitSharedBeta
: Fit model with a given shared beta for all genes
fitTwoTheta
: Fit model with two different thetas assigned to specific edges
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