powered by
The proc_colon function preprocesses colon gene expression data by:
proc_colon
Log transforming the raw counts.
Performing two-sample t-tests for each gene between normal and tumor samples.
Selecting the top 50 genes by absolute t-statistic.
Returning the filtered expression matrix and sample indices/groups.
proc_colon(colon, tissues)
A list with components:
A numeric matrix (samples x 50 genes) of selected, log‐transformed expression values.
Integer indices of normal‐tissue columns in the original data.
Integer indices of tumor‐tissue columns in the original data.
Integer vector of length ncol(colon), with 1 = normal, 2 = tumor.
ncol(colon)
A numeric matrix of raw colon gene expression values (genes × samples). Rows are genes; columns are samples.
A numeric vector indicating tissue type per sample: positive for normal, negative for tumor.
data("colon") data("tissues") set.seed(1234) colon_data <- proc_colon(colon, tissues) X <- colon_data$X # \donttest{ foo <- bmspcov(X, Sigma = cov(X)) sigmah <- estimate(foo) # }
Run the code above in your browser using DataLab