Plot a single gene expression histogram with best fitted mixture of t-distributions according to the EMMIX-gene algorithm.
plot_single_gene(
dat,
gene_id,
g = NULL,
random_starts = 8,
max_it = 100,
ll_thresh = 8,
min_clust_size = 8,
tol = 1e-04,
start_method = "both",
three = TRUE,
min = -4,
max = 2
)
A ggplot2 histogram with fitted t-distributions overlayed.
matrix of gene expression data.
row number of gene to be plotted.
force number of components, default = NULL
The number of random initializations used per gene when fitting mixtures of t-distributions. Initialization uses k-means by default.
The maximum number of iterations per mixture fit. Default value is 100.
The difference in -2 log lambda used as a threshold for selecting between g=1 and g=2 for each gene. Default value is 8, which was chosen arbitrarily in the original paper.
The minimum number of observations per cluster used when fitting mixtures of t-distributions for each gene. Default value is 8.
Tolerance value used for detecting convergence of EMMIX fits.
Default value is "both". Can also choose "random" for purely random starts.
Also test g=2 vs g=3 where appropriate. Defaults to TRUE.
Minimum and maximum x-axis values for the plot window.
example <- plot_single_gene(alon_data,1)
#plot(example)
Run the code above in your browser using DataLab