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Construct one or more neuroglancer annotation layers

Source: R/ng-annotations.R
ngl_annotation_layers.Rd

Construct one or more neuroglancer annotation layers

Usage

ngl_annotation_layers(ann, rawcoords = NA, colpal = NULL)

Arguments

ann

An annotation dataframe (see details) or any object containing 3D vertices from which xyzmatrix can successfully extract points.

rawcoords

Whether points have been provided in raw (voxel) coordinates or in calibrated (nm) positions. The default of NA will try to infer this based on the coordinate values but see details for limitations.

colpal

A function or named character vector of colours that will be used to set the colour for each layer. Colours should be specified by name or hex format.

Value

A list of additional class nglayers which can be added to an ngscene object as produced by ngl_decode_scene.

Details

If you supply a dataframe for the ann argument then you can have columns called

  • point or position or pt_position to define the position. This should contain x,y,z coordinates formatted as a character vector (xyzmatrix2str) or a list of numeric vectors (xyzmatrix2list).

  • layer optionally name a layer for each point

  • col optionally specify a color for each point.

  • root_id optionally specify a supervoxel id that the point maps onto

  • supervoxel_id optionally specify a supervoxel id that the point maps onto

Neuroglancer only allows one colour per annotation layer, so if you specify both col and layer they must be consistent.

Neuroglancer annotations are specified in raw coordinates. Although this function can try to convert nm coordinates to raw, this will only work for points in the brain space defined by the current fafb segmentation (see choose_segmentation). For this reason you should used rawcoords=FALSE and convert coordinates yourself if you are working with other brain spaces.

See also

ngl_annotations to extract annotations from a scene.

Examples

if (FALSE) { # \dontrun{
## as an example label proofread neurons by institution
psp=flywire_cave_query('proofreading_status_public_v1')
fwusers=googlesheets4::read_sheet('1G0zqA5DTrfd-a2LuebV4kcqNfl4q1ehlzHBrwT6ZMoc')
psp2=dplyr::left_join(psp, fwusers, by=c("user_id"="id"))
psp2$layer=psp2$institution
# sample 3000 neurons to be a more manageable as an example.
psp2s=dplyr::slice_sample(psp2, n=3000) %>%
  dplyr::filter(!is.na(layer))
# the layers will be rainbow coloured
al=ngl_annotation_layers(psp2s[c("pt_position", "layer")], colpal=rainbow)
# make a blank scene
sc=ngl_blank_scene()
# or decode a URL that you've copied from your browser
sc=ngl_decode_scene(clipr::read_clip())
# and the add your annotations as new layer(s) to that scene
sc2=sc+al
# and make a URL
u=as.character(sc2)
# and copy that to clipboard
clipr::write_clip(u)
# ... or open directly in your browser
browseURL(u)
# It is a good idea to shorten when there are many annotations.
# This will load much faster in the browser and be easier to work with
su=flywire_shortenurl(u)
browseURL(su)
} # }