View source: R/intercell_curated.R
curated_ligand_receptor_interactions | R Documentation |
The OmniPath intercell database annotates individual proteins and
complexes, and we combine these annotations with network interactions
on the client side, using import_intercell_network
. The
architecture of this database is complex, aiming to cover a broad range
of knowledge on various levels of details and confidence. We can use the
intercell_consensus_filter
and
filter_intercell_network
functions for automated, data
driven quality filtering, in order to enrich the cell-cell communication
network in higher confidence interactions. However, for many users, a
simple combination of the most established, expert curated ligand-receptor
resources, provided by this function, fits better their purpose.
curated_ligand_receptor_interactions(
curated_resources = c("Guide2Pharma", "HPMR", "ICELLNET", "Kirouac2010", "CellTalkDB",
"CellChatDB", "connectomeDB2020"),
cellphonedb = TRUE,
cellinker = TRUE,
talklr = TRUE,
signalink = TRUE,
...
)
curated_resources |
Character vector of the resource names which are considered to be expert curated. You can include any post-translational network resource here, but if you include non ligand-receptor or non curated resources, the result will not fulfill the original intention of this function. |
cellphonedb |
Logical: include the curated interactions from CellPhoneDB (not the whole CellPhoneDB but a subset of it). |
cellinker |
Logical: include the curated interactions from Cellinker (not the whole Cellinker but a subset of it). |
talklr |
Logical: include the curated interactions from talklr (not the whole talklr but a subset of it). |
signalink |
Logical: include the ligand-receptor interactions from SignaLink. These are all expert curated. |
... |
Passed to |
Some resources are a mixture of curated and bulk imported interactions, and sometimes it's not trivial to separate these, we take care of these here. This function does not use the intercell database of OmniPath, but retrieves and filters a handful of network resources. The returned data frame has the layout of interactions (network) data frames, and the source and target partners implicitly correspond to ligand and receptor. The data frame shows all resources and references for all interactions, but each interaction is supported by at least one ligand-receptor resource which is supposed to based on expert curation in a ligand-receptor context.
A data frame similar to interactions (network) data frames, the source and target partners being ligand and receptor, respectively.
import_intercell_network
filter_intercell_network
annotated_network
import_post_translational_interactions
import_ligrecextra_interactions
curated_ligrec_stats
lr <- curated_ligand_receptor_interactions()
lr
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.