Return pre and post counts in all the ROIs given bodyids innervate.
neuprint_get_roiInfo(
bodyids,
dataset = NULL,
all_segments = FALSE,
chunk = TRUE,
progress = FALSE,
conn = NULL,
...
)the body IDs for neurons/segments (bodies) you wish to query.
This can be in any form understood by neuprint_ids.
optional, a dataset you want to query. If NULL, the
default specified by your R environ file is used or, failing that the
current connection, is used. See neuprint_login for details.
if TRUE, all bodies are considered, if FALSE, only 'Neurons', i.e. bodies with a status roughly traced status.
A logical specifying whether to split the query into multiple
chunks or an integer specifying the size of those chunks (which defaults
to 2000 when chunk=TRUE).
default FALSE. If TRUE, the API is called separately for
each neuron and you can assess its progress, if an error is thrown by any
one bodyid, that bodyid is ignored
optional, a neuprintr connection object, which also specifies the
neuPrint server. If NULL, the defaults set in your
.Rprofile or .Renviron are
used. See neuprint_login for details.
methods passed to neuprint_login
a dataframe, one row for each given body id, columns ROI_pre and ROI_post for every ROI. If data is missing, NA is returned.
# \donttest{
neuprint_get_roiInfo(c(818983130, 1796818119))
#> # A tibble: 2 × 97
#> bodyid `LH(R).pre` `LH(R).post` `LH(R).downstream` `LH(R).upstream`
#> <int> <int> <int> <int> <int>
#> 1 818983130 211 97 2082 97
#> 2 1796818119 284 117 2554 117
#> # ℹ 92 more variables: `LH(R).mito` <int>, `LH(R).dark` <int>,
#> # `LH(R).medium` <int>, `SNP(R).pre` <int>, `SNP(R).post` <int>,
#> # `SNP(R).downstream` <int>, `SNP(R).upstream` <int>, `SLP(R).pre` <int>,
#> # `SLP(R).post` <int>, `SLP(R).downstream` <int>, `SLP(R).upstream` <int>,
#> # `MB(R).pre` <int>, `MB(R).post` <int>, `MB(R).downstream` <int>,
#> # `MB(R).upstream` <int>, `MB(R).mito` <int>, `MB(R).dark` <int>,
#> # `MB(R).light` <int>, `MB(R).medium` <int>, `CA(R).pre` <int>, …
# }