hybridization {MixThres} | R Documentation |
This function estimates the probe intensity values distribution using a particular mixture model in order to define in a second step a hybridization threshold.
hybridization(x, leftT = c(TRUE, FALSE, TRUE, FALSE), rightT = c(TRUE, TRUE, FALSE, FALSE), stop.crit = 1e-06, Kmax = 5)
x |
A dataframe containing a vector of probenames and a vector of probe intensity values. |
leftT |
A vector of boolean specifying the presence of a left truncature. |
rightT |
A vector of boolean specifying the presence of a right truncature of the same length than leftT. |
stop.crit |
The stopping relative precision limit for stopping EM algorithm. |
Kmax |
The maximal number of components in the mixture model. |
Truncated gaussian distributions are used. An EM algorithm with a supplement M-step corresponding to a fixed-point algorithm (in order to correct bias) is used to estimate the parameters of the mixture. A vector epsilon algorithm is used to accelerate the EM algorithm. The model is selected according to the BIC.
An object of class MixThres,
GeneID |
The vector of probenames. |
InputData |
The vector of input intensity values. |
ModelInfo |
A list concerning the selected model : nb of components, parameters estimation, loglikelihood, nb of parameters, aic, bic |
Prob |
The matrix of posterior probabilities. |
Trunc |
A vector of the two truncatures values. |
Bic |
A vector of the BIC calculated for all the models. |
NbParam |
A vector of the number of parameters for all the models. |
Crit |
NULL. Will be filled with the use of the threshold function. |
Threshold |
NULL. Will be filled with the use of the threshold function. |
Hybrid |
NULL. Will be filled with the use of the threshold function. |
J. Aubert
Picard et al., Using mixture models to define a hybridization threshold in DNA microarray experiments.
threshold
, print.MixThres
, plot.MixThres
, hist.MixThres
## Data simulation Signal <- c(rnorm(100,5,1),rnorm(700,8,1),rnorm(200,12,1)) fileIN <- data.frame(Gene=paste("Gene",1:1000,sep=""),Signal=Signal) ## Mixture models out <- hybridization(fileIN)