Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py

read_l2skel reads one or more neurons as simplified L2 skeletons.

read_l2dp reads one or more neurons as simplified dotprops format. See details.

Usage

read_l2skel(id, OmitFailures = TRUE, datastack_name = NULL, ...)

read_l2dp(id, OmitFailures = TRUE, datastack_name = NULL, ...)

Arguments

id

One or more flywire ids

OmitFailures

Whether or not to drop neurons that cannot be read from the results (rather than erroring out). Default TRUE.

datastack_name

A CAVE datastack_name. When missing will use the default implied by the segmentation chosen by choose_segmentation.

...

Additional arguments passed to the fafbseg.flywire.l2_skeleton or fafbseg.flywire.l2_dotpropsfunctions.

Details

read_l2dp is generally recommended rather than fetching a skeleton and then calculating dotprops because it is much faster and also computes better direction vectors. However if you wish to simplify a skeleton (e.g. to find the cell body fibre) then you will need to take the two step approach. This also has the possible advantage that you can specify the step size at which direction vectors are generated along the neuron. Note also that read_l2dp may drop some regions of the neuron (likely thin ones) that define only a very small mesh volume.

These functions depends on Philipp Schlegel's fafbseg-py package. You can install this using simple_python.

The datastack_name argument is optional because the correct datastack name and corresponding cloud volume URL will be read from options set by choose_segmentation; this is generally the preferred way for end users to select an active dataset. Neverthless, if a datastack_name it will be used to look up the correct segmentation URL and fafbseg-py will be correctly set up using these two pieces of information.

Examples

if (FALSE) {
# install full set of recommended packages including fafbseg-py
simple_python("full")
kcsvids=c("78603674556915608", "78462662124123765", "77547662357982001",
"78533168373869635", "78251418452635714", "78323024281482155",
"78322062208411707", "78533649477402370", "77829412279715493",
"77899643517979532", "78814230967028270", "78533993141739277",
"78041274292494941", "78252449311896359", "77618924522629940",
"77618237260576979", "78673768356594679", "78182148951479619",
"78392293379997680", "77688812230426430")
kcids=flywire_rootid(kcsvids)
kcs=read_l2skel(kcids)

library(nat.nblast)
kcdps=read_l2dp(kcids)
# nb these are in microns
boundingbox(kcdps)
kcaba=nblast_allbyall(kcdps)
kchc=nhclust(scoremat = kcaba)
plot(kchc)
# 3d plot using the skeletons rather than dotprops versions of the neurons
# gamma neurons seprate from the rest
plot3d(kchc, k=2, db=kcs)
}