est_phats {dtangle} | R Documentation |
Estimate the gene type proportions.
est_phats(Y, markers, baseline_ests, gamma, summary_fn = mean,
inv_scale = function(x) 2^x)
Y |
Expression matrix. (Required) Two-dimensional numeric. Must implement Each row contains expression measurements for a particular sample. Each columm contains the measurements of the same gene over all individuals. Can either contain just the mixture samples to be deconvolved or both the mixture samples and the reference samples. See |
markers |
Marker gene indices. (Optional) List of one-dimensional integer. Top-level list should be same length as |
baseline_ests |
List of vectors (same structure as markers). One list entry for each cell type. Each list element is a vector of estimated offset for each marker of the respective type (output from |
gamma |
Expression adjustment term. (Optional) One-dimensional positive numeric. If provided as a single positive number then that value will be used for |
summary_fn |
What summary statistic to use when aggregating expression measurements. (Optional) Function that takes a one-dimensional vector of numeric and returns a single numeric. Defaults to the mean. Other good options include the median. |
inv_scale |
Inverse scale transformation. Default to exponential as dtangle assumes data has been logarithmically transformed. |
Estimated matrix of mixing proportions.
truth = shen_orr_ex$annotation$mixture
pure_samples <- lapply(1:3, function(i) {
which(truth[, i] == 1)
})
Y <- shen_orr_ex$data$log
markers = find_markers(Y=Y,pure_samples = pure_samples,
data_type='microarray-gene',marker_method='ratio')$L
K = length(pure_samples)
n_markers = rep(20,K)
mrkrs <- lapply(1:K, function(i) {
markers[[i]][1:n_markers[i]]
})
baseline = dtangle:::baseline_exprs(Y, pure_samples, mrkrs)
phats <- dtangle:::est_phats(Y, mrkrs, baseline, gamma=.8)