Function reference • catnat

Package information
`catnat-package`	catnat: Analyse neuronal morphology and connectivity (extends catmaid and nat)
CATMAID API Functions to interact with CATMAID API. These typically build on the existing catmaid R package.
`catmaid_annotate_partners()` `catmaid_get_annotated_partner()` `reverse.name.side()`	Annotate CATMAID partners
`catmaid_connector_nodes()`	Get information on a CATMAID connector node
`catmaid_controlled_upload()`	Interactively upload neuron(s) to CATMAID
`catmaid_delete_neuron()` `catmaid_delete_connectors()` `catmaid_delete_neurons()`	Function used to delete single neurons from CATMAID based on a given skeleton ID
`catmaid_find_likely_merge()`	Find the TODO tagged merge sites between a given neuron and the CATMAID database at large
`catmaid_get_neuronid()`	Get the CATMAID neuron ID that corresponds to the skeleton ID
`catmaid_get_server()`	Get CATMAID server
`catmaid_get_tag()`	Find the location of specified tags for a CATMAID neuron
`catmaid_interactive_join()`	Interactively choose to join neurons in CATMAID, visualising with rgl in R
`catmaid_join_skeletons()`	Programmatically join CATMAID skeletons
`catmaid_link_connectors()`	Add synaptic links between connectors and treenodes
`catmaid_lock_neurons()` `catmaid_unlock_neurons()`	Lock or unlock a CATMAID neuron reconstruction
`catmaid_node_time()`	Get the UTC creation / edit time for a CATMAID node
`catmaid_set_meta_annotations()`	Meta-annotate CATMAID annotations
`catmaid_skeletons_in_bbx()`	Search for CATMAID skeletons within a volume
`catmaid_update_radius()` `fafbseg_update_node_radii()`	Update radius information for tree nodes in a CATMAID instance
`catmaid_upload_neurons()`	Upload neuron(s) to CATMAID
Autosegmentation Convenience functions for working with autosegmentation results
`fafb_frags_ids()` `fafb_frags_skeletons()` `fafb_seg_hitlist()` `fafb_seg_tracing_list()`	Fetch the up or outgoing auto-traced FAFB fragments from a CATMAID FAFB neuron
`fafb_seg()`	Use any CATMAID function in the v14-seg environment, without logging into separate CATMAID instance
`fafb_seg_conn()`	Log into the v14-seg CATMAID instance for FAFB v14 Adult flybrain segmented skeletonisations
`fafb_segs_stitch_volumes()` `neuronvolume3d()`	Get neuron volumes and stitch them into a cohesive neuron, or neuronal compartment
`fafbseg_join_connectors_in_ngl_volumes()`	Join free connectors in a CATMAID instance to skeletons if they share a Google Brainmaps volume
`fafbseg_transfer_tags()` `fafbseg_transfer_connectors()`	Transfer information between v14 and v14-seg neurons
`read.neurons.fafbseg()` `fafbseg_get_node_count()`	Read neurons from the FAFB segmentation instance (temporary)
Uncategorised functions
`WriteVTKalphashape()`	Write alphashape as a .vtk file
`arbour.clusters()` `arbours()`	Segregate neurite compartments from a neuron/neuronlist based on synapse clustering
`as.mesh3d(<kde>)`	Convert a 3D Kernel Density Estimate (package ks) into rgl mesh3d object
`ashape2mesh3d()`	Convert an alpha shape to a mesh3D object
`assign.connector.info()`	Give connector data in a CATMAID neuron the same attributes as node data
`assign_cable.polarity()`	Assign axon/dendrite split to skeletons
`assign_lh_neuron()` `scan_lh_matches()`	Assign identity to lateral horn neurons
`assign_strahler()`	Assign Strahler stream order to neurites
`assignside()`	Assign cell body side based on neuron name
`average.tracts()`	Average non-branching tracts
`cluster_synapses_within_skeleton()`	Cluster synapses within a neuron's skeleton
`clusterbysynapses()`	Cluster neurons by pre- and postsynapse positions
`combine.alphashape()`	Combine alphashapes generated by the alphashapes package
`skeleton_connectivity_matrix()` `connectivity_matrix()` `neuron.heatmap()`	Generate connectivity matrix
`connectivity_similarity()` `connectivity_similarity_distance()` `connectivity_similarity_matrix()`	Calculate a connectivity similarity score between two connectivity profiles
`connector_URL()`	Generate URLs to CATMAID connector location
`node.contribution.to.skeletons()` `synapse.contribution.to.skeletons()`	Get data tracers' contributions to skeletons
`correctsoma()`	Re-root neurons to their soma
`create_skeleton_from_nrrd()`	Create a skeleton from a skeletonised neuron saved as a .Nrrd file
`create_tracing_samplesheet()` `update_single_samplesheet()` `update_tracing_samplesheets()`	Create or update a googlesheet of randomised tracing targets for a given neuron
`distance.from.first.branchpoint()`	Calculate geodesic distance from nodes to a neuron's axon-dendrite branchpoint
`downstream.deletion.test()`	Find how many downstream partners tracers have connected up
`axonic_points()` `dendritic_points()` `mixed_points()` `primary_dendrite_points()` `axonal_endings()` `dendritic_endings()` `axonic_endings()` `primary_dendrite_endings()` `axonic_cable()` `dendritic_cable()` `arbour_cable()` `unsure_cable()` `primary_dendrite_cable()`	Extract axonic/dendritic points/cable from a neuron/neuronlist
`flow.centrality()`	Determine dendritic/axonal by calculating flow centrality
`get.hxsurf()`	Read Amira surface (aka HxSurface or HyperSurface) files into hxsurf object
`get.skeleton.from.flycircuit()` `reroot.flycircuit.neuron()` `Chiang2FCWB()`	Fetch FlyCircuit neuron skeletons from the Taiwan FlyCircuit server
`get.synapses()`	Get 3D coordinates of synapse (not connector) positions
`get_connected_skeletons()`	Retrieving CATMAID neuron skeletons connected to query skeletons
`inside_neuropils()` `points_in_neuropil()` `in_neuropil()`	Calculate the cable length inside of different neuropils in a segmented .surf brain
`label_neuron.class()`	See neurons with chosen neuropils to determine their types
`local_conn()`	Connect to a local CATMAID server
`make.anatomical.model()`	Generate a neuroanatomical alpha shape from connector and/or tree node data
`make.mirror.transform()`	Get the transformation matrix from the Morpho::mirror function
`manually_assign_axon_dendrite()` `plot3d(<split>)`	Manually assign the dendrite and axon to a neuron
`map_fafbsegs_to_neuron()`	Find out what is already known about a neuron's connectivity profile and connected FAFB segments
`mark.microtubules()` `prune_microtubules()` `visualise.microtubules()` `microtubules.errors()`	Functions to assign and visualise microtubule rich and twig portions of a neuron
`napplyTransform()`	Apply a transform to a neuron/neuronlist
`nblast_bothways()`	NBLAST two different sets of neurons forwards and backwards
`neurites()`	Segregate neurite compartments from a neuron/neuronlist
`neurons.inside()`	Find neurites inside of an alphashape
`open_l1()`	Jump from R into the L1 larval EM data in CATMAID
`overlap.connectivity.matrix()` `overlap.connectivity.matrix.catmaid()`	Generate a connectivity matrix based on euclidean distance between points
`pointsinsidemesh()`	Find neurites inside of an mesh3d object
`primary.neurite()` `starting.neurite()`	Returns the primary neurite of a neuron
`prune(<catmaidneuron>)`	Prune nodes from a catmaid neuron, keeping the synapses
`prune_by_tag()`	Prune neuron by splitting it at CATMAID tags
`prune_distal()`	Prune nodes from a neuron, keeping the root node
`prune_in_volume()`	Prune neuron within neuropil volume
`prune_online()`	Prune a neuron interactively
`prune_strahler.catmaidneuron()`	Prune a CATMAID neuron by removing segments with a given Strahler order
`prune_vertices.catmaidneuron()`	Prune vertices from a CATMAID neuron, keeping the synapses
`resample(<catmaidneuron>)`	Resample a CATMAID neuron
`rescue.dps()`	Generate a dps object without dropping small neurons
`scan4matching()`	Scan through suggested pairs of neurons
`seebroken3d()`	Plot neurons split up by synapse clusters
`seesplit3d()` `splitscan()`	Plot neurons split up by flow centrality
`select_neurons()` `deselect_neurons()`	Select neurons in space
`select_points()`	Select 3D points in space
`set_segmentation_location()`	Calculate a connectivity similarity score between two connectivity profiles
`shift.neurons()`	Shift neurons in space
`sholl_data()`	Sholl analysis on neuron skeletons
`soma()` `somaid()` `somapos()`	Functions for retrieving soma data
`subtree()`	Get a subtree in a neuron object as a separate neuron object
`synapsecolours.neuron()`	Plot a neuron with different coloured synapses depending on partners
`tracer.plot()` `tracer.treenodes.plot()` `tracer.neuron.stats()`	Get data and plots describing tracer activity statistics
`transform3dalphashape()`	Transform the 3D vertices of an alphashape
`update_neurons()` `update_names()`	Update a local neuronlist with new CATMAID data
`write.spin.split.swc()` `write.spin.swc()`	Write ordered swc

Reference

Package information

CATMAID API

Autosegmentation

Uncategorised functions

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