TF-target interactions from CollecTRI

CollecTRI is a comprehensive resource of transcriptional regulation, published in 2023, consisting of 14 resources and original literature curation.

Usage

collectri(...)

Arguments

...

Arguments passed on to omnipath_query

organism: Character or integer: name or NCBI Taxonomy ID of the organism. OmniPath is built of human data, and the web service provides orthology translated interactions and enzyme-substrate relationships for mouse and rat. For other organisms and query types, orthology translation will be called automatically on the downloaded human data before returning the result.
resources: Character vector: name of one or more resources. Restrict the data to these resources. For a complete list of available resources, call the `get_<query_type>_resources` functions for the query type of interst.
genesymbols: Character or logical: TRUE or FALS or "yes" or "no". Include the `genesymbols` column in the results. OmniPath uses UniProt IDs as the primary identifiers, gene symbols are optional.
fields: Character vector: additional fields to include in the result. For a list of available fields, call `query_info("interactions")`.
default_fields: Logical: if TRUE, the default fields will be included.
silent: Logical: if TRUE, no messages will be printed. By default a summary message is printed upon successful download.
logicals: Character vector: fields to be cast to logical.
format: Character: if "json", JSON will be retrieved and processed into a nested list; any other value will return data frame.
download_args: List: parameters to pass to the download function, which is `readr::read_tsv` by default, and `jsonlite::safe_load`.
references_by_resource: Logical: if TRUE,, in the `references` column the PubMed IDs will be prefixed with the names of the resources they are coming from. If FALSE, the `references` column will be a list of unique PubMed IDs.
add_counts: Logical: if TRUE, the number of references and number of resources for each record will be added to the result.
license: Character: license restrictions. By default, data from resources allowing "academic" use is returned by OmniPath. If you use the data for work in a company, you can provide "commercial" or "for-profit", which will restrict the data to those records which are supported by resources that allow for-profit use.
password: Character: password for the OmniPath web service. You can provide a special password here which enables the use of `license = "ignore"` option, completely bypassing the license filter.
exclude: Character vector: resource or dataset names to be excluded. The data will be filtered after download to remove records of the excluded datasets and resources.
json_param: List: parameters to pass to the `jsonlite::fromJSON` when processing JSON columns embedded in the downloaded data. Such columns are "extra_attrs" and "evidences". These are optional columns which provide a lot of extra details about interactions.
strict_evidences: Logical: reconstruct the "sources" and "references" columns of interaction data frames based on the "evidences" column, strictly filtering them to the queried datasets and resources. Without this, the "sources" and "references" fields for each record might contain information for datasets and resources other than the queried ones, because the downloaded records are a result of a simple filtering of an already integrated data frame.
genesymbol_resource: Character: "uniprot" (default) or "ensembl". The OmniPath web service uses the primary gene symbols as provided by UniProt. By passing "ensembl" here, the UniProt gene symbols will be replaced by the ones used in Ensembl. This translation results in a loss of a few records, and multiplication of another few records due to ambiguous translation.
cache: Logical: use caching, load data from and save to the. The cache directory by default belongs to the user, located in the user's default cache directory, and named "OmnipathR". Find out about it by omnipath_get_cachedir. Can be changed by omnipath_set_cachedir.

Value

A dataframe of TF-target interactions.

Examples

collectri_grn <- collectri()
collectri_grn
#> # A tibble: 64,495 × 15
#>    source  target source_genesymbol target_genesymbol is_directed is_stimulation
#>    <chr>   <chr>  <chr>             <chr>                   <dbl>          <dbl>
#>  1 P01106  O14746 MYC               TERT                        1              1
#>  2 P17947  P02818 SPI1              BGLAP                       1              1
#>  3 COMPLE… P05412 FOSL1_JUNB        JUN                         1              1
#>  4 COMPLE… P05412 FOS_JUN           JUN                         1              1
#>  5 COMPLE… P05412 FOS_JUNB          JUN                         1              1
#>  6 COMPLE… P05412 FOSL2_JUND        JUN                         1              1
#>  7 COMPLE… P05412 FOSL2_JUN         JUN                         1              1
#>  8 COMPLE… P05412 JUN               JUN                         1              1
#>  9 COMPLE… P05412 FOSB_JUNB         JUN                         1              1
#> 10 COMPLE… P05412 JUNB              JUN                         1              1
#> # ℹ 64,485 more rows
#> # ℹ 9 more variables: is_inhibition <dbl>, consensus_direction <dbl>,
#> #   consensus_stimulation <dbl>, consensus_inhibition <dbl>, sources <chr>,
#> #   references <chr>, curation_effort <dbl>, n_references <dbl>,
#> #   n_resources <int>

Usage

Arguments

Value

See also

Examples