View source: R/DEGGs_core_functions.R
generate_subnetworks | R Documentation |
Generate subgroup specific gene-gene interaction networks with interaction p values
generate_subnetworks(
normalised_counts,
metadata,
subgroup_variable,
regression_method = "rlm",
subgroups = NULL,
network = NULL,
entrezIDs = FALSE,
convert_to_gene_symbols = TRUE,
use_qvalues = FALSE,
cores = parallel::detectCores()/2
)
normalised_counts |
a data frame containing normalised counts from an
high throughput sequencing experiment.
Sample IDs must be in columns and gene/miRNA/TFs in rows.
Objects of class |
metadata |
a data frame of sample data with rownames matching the
sample IDs in |
subgroup_variable |
column name in |
regression_method |
whether to use robust linear modelling to calculate link p values. Options are 'rlm' (default) or 'lm'. |
subgroups |
optional character vector indicating which subgroups
must be used for comparison. If not specified, all subgroups in
|
network |
network of biological interactions provided by the user. The
network must be provided in the form of a table of class data.frame with two
columns named "from" and "to".
If NULL (default) a network of 10,537 molecular interactions obtained from
KEGG, mirTARbase, miRecords and transmiR will be used.
This has been obtained via the |
entrezIDs |
logical (default FALSE) used to define whether gene ids in
|
convert_to_gene_symbols |
logical to be used when using entrez ids. If TRUE (default), the output will show gene symbols. |
use_qvalues |
whether to use Storey's q values for multiple test adjustment. If FALSE (default), unadjusted p values will be used and shown in the output. |
cores |
number of cores to use. |
a deggs
object containing subgroup specific networks incorporating
p values or adjusted p values for each link.
deggs
.
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