View source: R/net_and_modules.R
build_net | R Documentation |
Compute the adjacency matrix, then the TOM to build the network. Than detect the modules by hierarchical clustering and thresholding
build_net(
data_expr,
fit_cut_off = 0.9,
cor_func = c("pearson", "spearman", "bicor", "other"),
your_func = NULL,
power_value = NULL,
block_size = NULL,
stop_if_fit_pb = FALSE,
pct_power_ic = 0.7,
network_type = c("unsigned", "signed", "signed hybrid"),
tom_type = c("unsigned", "signed", "signed Nowick", "unsigned 2", "signed 2", "none"),
keep_matrices = c("none", "cor", "adja", "both"),
n_threads = NULL,
...
)
data_expr |
matrix or data.frame or SummarizedExperiment, expression data with genes as column and samples as row. |
fit_cut_off |
float, cut off by which R^2 (coefficient of determination) will be thresholded. Must be in ]0;1[. |
cor_func |
string, name of the correlation function to be used. Must be one of "pearson", "spearman", "bicor", "other". If "other", your_func must be provided |
your_func |
function returning correlation values. Final values must be in [-1;1] |
power_value |
integer, power to be applied to the adjacency matrix. If NULL, will be estimated by trying different power law fitting. |
block_size |
integer, size of blocks by which operations can be proceed. Helping if working with low capacity computers. If null, will be estimated. |
stop_if_fit_pb |
boolean, does not finding a fit above fit_cut_off, or having a power too low or too high (based on WGCNA FAQ recommended powers) should stop process, or just print a warning and return the highest fitting power. |
pct_power_ic |
float, confidence interval by which the power fitted should be evaluated for too high or too low a power. |
network_type |
string, type of network to be used. Either "unsigned", "signed", "signed hybrid". See details. |
tom_type |
string, type of the topological overlap matrix to be
computed. Either "none", "unsigned", "signed", "signed Nowick",
"unsigned 2", "signed 2" and "signed Nowick 2". See detail at
|
keep_matrices |
string, matrices to keep in final object. Can be one of
"none", "cor", "adja", "both". It is usefull to keep both if you plant to use
|
n_threads |
integer, number of threads that can be used to paralellise the computing |
... |
any other parameter compatible with
|
list containing network matrix, metadata of input parameters and power fitting information.
net <- build_net(kuehne_expr[, seq_len(350)], n_threads = 1)
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