Filters a data frame retrieved by intercell
.
Usage
filter_intercell(
data,
categories = NULL,
resources = NULL,
parent = NULL,
scope = NULL,
aspect = NULL,
source = NULL,
transmitter = NULL,
receiver = NULL,
secreted = NULL,
plasma_membrane_peripheral = NULL,
plasma_membrane_transmembrane = NULL,
proteins = NULL,
causality = NULL,
topology = NULL,
...
)
Arguments
- data
An intercell annotation data frame as provided by
intercell
.- categories
Character: allow only these values in the
category
column.- resources
Character: allow records only from these resources.
- parent
Character: filter for records with these parent categories.
- scope
Character: filter for records with these annotation scopes. Possible values are
generic
andspecific
.- aspect
Character: filter for records with these annotation aspects. Possible values are
functional
andlocational
.- source
Character: filter for records with these annotation sources. Possible values are
composite
andresource_specific
.- transmitter
Logical: if
TRUE
only transmitters, ifFALSE
only non-transmitters will be selected, ifNULL
it has no effect.- receiver
Logical: works the same way as
transmitters
.- secreted
Logical: works the same way as
transmitters
.- plasma_membrane_peripheral
Logical: works the same way as
transmitters
.- plasma_membrane_transmembrane
Logical: works the same way as
transmitters
.- proteins
Character: filter for annotations of these proteins. Gene symbols or UniProt IDs can be used.
- causality
Character: filter for records with these causal roles. Possible values are
transmitter
andreceiver
. The filter applied simultaneously to thetransmitter
andreceiver
arguments, it's just a different notation for the same thing.- topology
Character: filter for records with these localization topologies. Possible values are
secreced
,plasma_membrane_peripheral
andplasma_membrane_transmembrane
; the shorter notationssec
,pmp
andpmtm
can be used. Has the same effect as the logical type arguments, just uses a different notation.- ...
Ignored.
Examples
ic <- intercell()
ic <- filter_intercell(
ic,
transmitter = TRUE,
secreted = TRUE,
scope = "specific"
)
#> Removed 329240 and kept 3207 records of intercell data.