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diff --git a/.gitignore b/.gitignore
@@ -2,5 +2,7 @@
 .Rhistory
 .RData
 .Ruserdata
+docs
+inst/doc
 data-raw/*
 data/crant_data.sqlite
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -47,27 +47,17 @@ Suggests:
     usethis,
     rmarkdown,
     spelling,
-    arrow,
-    ggnewscale (>= 0.4.10.9000),
-    ggpubr,
-    catmaid,
     grDevices,
-    nabor,
-    fs,
-    purrr,
     plyr
 Remotes: 
     natverse/nat,
     natverse/fafbseg@asb-dev,
     natverse/nat.flybrains,
     natverse/nat.templatebrains,
-    catmaid=natverse/rcatmaid,
     natverse/malevnc,
     flyconnectome/fancr,
     flyconnectome/bancr,
-    kassambara/ggpubr,
-    tidyverse/ggplot2,
-    eliocamp/ggnewscale
+    tidyverse/ggplot2
 Config/testthat/edition: 3
 LazyDataCompression: xz
 Encoding: UTF-8

diff --git a/README.md b/README.md
@@ -7,22 +7,17 @@
 crantr
 ===========
 
-**crantr** is an R package designed to support the analysis of connectome data sets for the clonal raider ant (*Ooceraea biroi*, formerly *Cerapachys biroi*). The package primarily focuses on proofread auto-segmentation data from the [CRANT (Clonal Raider Ant) project](https://proofreading.zetta.ai/info/api/v2/datastack/full/kronauer_ant?middle_auth_url=proofreading.zetta.ai%2Fsticky_auth).
+**crantr** is an R package designed to support the analysis of connectome data sets for clonal raider ants (*Ooceraea biroi*, formerly *Cerapachys biroi*). The package primarily focuses on proofread auto-segmentation data from the [CRANT (Clonal Raider Ant) project](https://proofreading.zetta.ai/info/api/v2/datastack/full/kronauer_ant?middle_auth_url=proofreading.zetta.ai%2Fsticky_auth).
 This project has a community based in the [CRANT slack](https://app.slack.com/client/T07RC68DXQA/C07S10GRL9W).
-The project was founded as a collaboration between the laboratories of [Wei-Chung Allen Lee](https://www.lee.hms.harvard.edu/), 
-[Daniel Kronauer](https://www.rockefeller.edu/our-scientists/heads-of-laboratories/988-daniel-kronauer/) and [Hannah Haberkern](https://www.research-in-bavaria.de/research-news/details/article/new-junior-research-group-hannah-haberkern-investigates-navigation-in-flies-and-ants/),
-among others. 
-The project lead is [Lindsey Lopes](https://www.linkedin.com/in/lindsey-e-lopes-a16a3292/). 
-For the time being, there is a single ant brain connectome under construction,`CRANTb`.
 
 ### About Clonal Raider Ants
 
 Clonal raider ants (*Ooceraea biroi*) are a fascinating species of ant known for their unique reproductive biology and social structure:
 
-- They reproduce clonally via parthenogenesis.
-- They lack a queen caste, and all workers in a colony lay eggs.
-- They exhibit complex social behaviors, including division of labor, chemical communication, and parental care.
-- It is possible to make [mutant](https://www.cell.com/fulltext/S0092-8674(17)30772-9) and [transgenic](https://www.cell.com/fulltext/S0092-8674(17)30772-9) ants.
+- They reproduce through parthenogenesis, meaning all individuals are female clones.
+- They lack a queen caste, with all individuals capable of laying eggs.
+- They alternate between reproductive and brood care phases in synchronized cycles.
+- They exhibit collective hunting behavior, raiding other ant colonies for their larvae.
 
 These characteristics make clonal raider ants an excellent model system for studying the neural basis of social behavior and the evolution of eusociality in insects.
 
@@ -36,15 +31,15 @@ The **crantr** package serves as a wrapper over the [fafbseg](https://github.com
 
 1. Setup of necessary default paths / data redirects.
 2. Integration with [CAVE tables](https://proofreading.zetta.ai/info/) for storing various annotation information.
-3. Relevant helper functions called from the [bancr](https://github.com/flyconnectome/crantr) package.
-3. CRANT project specific data wrangling and browsing code.
+3. Relevant helper functions called from the [bancr](https://github.com/flyconnectome/bancr) package.
+3. CLANT project specific data wrangling and browsing code.
 
 ## Installation
 
 You can install the development version of `crantr` from GitHub:
 
 ```r
-remotes::install_github('flyconnectome/crantr')
+remotes::install_github('natverse/crantr')
 ```
 
 ### Authorisation
@@ -70,7 +65,7 @@ To ensure everything is set up correctly, run:
 dr_crant()
 
 # Confirm functionality (should return FALSE)
-crant_islatest("576460752703346048")
+crant_islatest("576460752684030043")
 ```
 
 ### Python Dependencies
@@ -79,8 +74,6 @@ Some functions rely on underlying Python code. To install the full set of recomm
 
 ```r
 fafbseg::simple_python("full")
-fafbseg::simple_python('none', pkgs='numpy~=1.23.5')
-fafbseg::simple_python(pkgs="pcg_skel")
 ```
 
 If you encounter errors related to cloud-volume, update it with:
@@ -91,43 +84,34 @@ fafbseg::simple_python('none', pkgs='cloud-volume~=8.32.1')
 
 ## Usage
 
-Use `with_crant()` to wrap additional `fafbseg::flywire_*` functions for use with CRANT data. 
-
-Alternatively, use `choose_crant()` to set all `flywire_*` functions from `fafbseg` to target CRANT.
-
-Usefully the package contains the main use cases, functions named like `crant_*`. 
-This is likely the main way you want to use this package.
+Use `with_crant()` to wrap additional `fafbseg::flywire_*` functions for use with CRANT data. Alternatively, use `choose_crant()` to set all `flywire_*` functions from `fafbseg` to target CRANT.
 
 Example:
 
 ```r
 library(crantr)
 choose_crant()
 
-# Your analysis code here, .e.g.
-neuron.mesh <- crant_read_neuron_meshes("576460752684030043")
-plot3d(neuron.mesh, col = "purple")
+# Your analysis code here
 ```
 
-![crantb_example_neuron](https://github.com/flyconnectome/crantr/blob/main/inst/images/crantb_example_neuron.png?raw=true)
-
 ## Updating
 
 To update the package and all dependencies:
 
 ```r
-remotes::install_github('flyconnectome/crantr')
+remotes::install_github('natverse/crantr')
 ```
 
 To update a specific Python library dependency:
 
 ```r
-fafbseg::simple_python(pkgs='pcg_skel')
+fafbseg::simple_python(pkgs='fafbseg')
 ```
 
 ## Tutorial
 
-Project lead [Lindsey E. Lopes](https://www.linkedin.com/in/lindsey-e-lopes-a16a3292/) in the [Laboratory of Social Evolution and Behavior](https://www.rockefeller.edu/our-scientists/heads-of-laboratories/988-daniel-kronauer/) is interested in the olfactory system of the ant, and so some of the earliest reconstruction was done in the ant antennal lobe.
+Lindsey Lopes in the Kronauer group is interested in the olfactory system of the ant, and so some of the earliest reconstruction was done in the ant antennal lobe.
 
 Let us look at some antennal lobe projection neurons.
 
@@ -138,10 +122,7 @@ If you are a collaborator on the project and have access to our [seatable](https
 library(crantr)
 
 # get meta data, will one dya be available via CAVE tables
-ac <- crant_table_query()
-
-# Quickly update all of our IDs
-ac <- crant_updateids(ac)
+ac <- anttable_query()
 
 # have a look at it!
 View(ac)
@@ -163,11 +144,7 @@ library(crantr)
 # specify IDs to examine, could also be gotten from a CAVE table
 pn.ids <- c("576460752684030043", "576460752688452399", "576460752688452655", 
 "576460752666304186", "576460752683636730", "576460752724736013")
-```
-
-You can do important operations such as update the 'root' IDs for a CRANT reconstruction, as so.
 
-```r
 # update these IDs to their most current versions, they change after each proofreading edit
 pn.ids <- crant_latestid(pn.ids)
 ```
@@ -185,24 +162,18 @@ plot3d(crantb.surf, col = "lightgrey", alpha = 0.1)
 # plot neurons
 plot3d(pn.meshes)
 ```
-![crantb_example_neuron_meshes](https://github.com/flyconnectome/crantr/blob/main/inst/images/crantb_example_neuron_meshes.png?raw=true)
 
 We can also make this plot in 2D, in the popular `ggplot2` framework.
 
 ```r
 # ggplot
 crant_ggneuron(pn.meshes , volume = crantb.surf)
 ```
-![crantb_example_neuron_ggplot](https://github.com/flyconnectome/crantr/blob/main/inst/images/crantb_example_neuron_ggplot.png?raw=true)
 
 Sometimes it is also useful for work with skeletons, for example for NBLASTing neurons. We can swiftly fetch the L2 skeletons of a neuron,
-built from its supervoxel locations using the python library [pcg_skel](https://github.com/AllenInstitute/pcg_skel), as so:
+built from its super-voxel locations using the python library [pcg_skel](https://github.com/AllenInstitute/pcg_skel), as so:
 
 ```r
-# You may need to run this before the belows works, should just need it once:
-## fafbseg::simple_python('none', pkgs='numpy~=1.23.5')
-## fafbseg::simple_python(pkgs="pcg_skel")
-
 # fetch
 pn.skels <- crant_read_l2skel(pn.ids)
 
@@ -213,92 +184,9 @@ plot3d(crantb.surf, col = "lightgrey", alpha = 0.1)
 
 # plot neurons
 plot3d(pn.skels, lwd = 1)
+plot3d(pn.meshes, alpha = 0.1)
 ```
-![crantb_example_neuron_skeletons](https://github.com/flyconnectome/crantr/blob/main/inst/images/crantb_example_neuron_skeletons.png?raw=true)
-
-These are the raw ingredients to start morphological analyses in `CRANTb` using the [natverse](https://natverse.org/)! 
-
-We hope to come: neuron annotations, synapses, transmitter predictions, dense core vesicle predictions, possibly other organelles, etc ....
-
-## Meta data management in seatable
 
-![ant_table](https://github.com/flyconnectome/crantr/blob/main/inst/images/ant_table.png?raw=true)
-
-Seatable is a powerful way to make collaborative annotations in this connectome dataset and we encourage you to use it rather than keeping your own google sheets or similar to track neurons.
-It works similarly to google sheets, but has better filter views, data type management, programmatic access, etc. 
-It should work in the browser and as an [app](https://seatable.io/en).
-
-See our seatable [here](https://cloud.seatable.io/workspace/62919/dtable/CRANTb/?tid=0000&vid=0000).
-If this link does not work you can request access by contacting Lindsey Lopes.
-
-Each row is a `CRANTb` neuron. If you hover your tool-tip over the **i** icon in each column header, you can see what that column records.
-Each neuron is identified by its unique 16-digit integer `root_id`, which is modified each time the neuron is edited.
-As `CRANTb` is an active project, this happens frequently so our seatable needs to keep track of changes, which it does on a daily schedule.
-
-The update logic is `position` (voxel space) -> `supervoxel_id` -> `root_id`.
-If `position` and `supervoxel_id` are missing, `root_id` is updated directly but this is longer. 
-It will also take the most up to date `root_id` with the most number of voxels from the previous root_id, so if a neuron is split this could be the incorrect choice. 
-Updating from `position` gives you the neuron at that position, regardless of its size, merges or splits.
-Best practice is to add position always if you can, and `root_id` in addition if you want. 
-You may want to add only `root_id` alone if you want to track a neuron but do not yet have a good position for it. 
-A good position is a point on the neuron that you expect not to change during proofreading, e.g. the first branch point in the neuron where it splits from the primary neurite into axon and dendrite.
-
-![ant_table_ids](https://github.com/flyconnectome/crantr/blob/main/inst/images/ant_table_ids.png?raw=true)
-
-You can access the seatable programmatically using the `crantr`, if you have access.
-
-```r
-remotes::github_install('flyconnectome/crantr')
-library(crantr)
-```
-
-You will first need to obtain your authorised login credentials, you only need to do this once:
-
-```r
-crant_table_set_token(user="MY_EMAIL_FOR_SEATABLE",
-               pwd="MY_SEATABLE_PASSWORD",
-               url="https://cloud.seatable.io/")
-```
-
-And then you may read the data, and make nice plots from it!
-
-```r
-# Read BANC meta seatable
-ac <- crant_table_query()
-```
-
-You can also update rows automatically. Be careful when doing this. If you want to be sure not to mess something up, 
-you can take a 'snapshot' of the seatable before you edit it in the browser, which will save a historical version.
-
-You can then change columns in `ac`, keeping their names, as you like. Then to update via R:
-
-```r
-# Update
-crant_table_update_rows(base="CRANTb", 
-                     table = "CRANTb_meta", 
-                     df = ac.new, 
-                     append_allowed = FALSE, 
-                     chunksize = 100)
-```
-
-
-To update, you must have the seatable identifier for each column in `ac.new`, i.e. an `_id` column.
-
-This method is good for bulk uploads/changes.
-
-You can also make a quick, simpler update, replacing one column's entries with a given `update` for a set of root IDs.
-
-```r
-crant_table_annotate(root_ids = c("576460752667713229",
-                               "576460752662519193",
-                               "576460752730083020",
-                               "576460752673660716",
-                               "576460752662521753"),
-                  update = "lindsey_lopes",
-                  overwrite = FALSE,
-                  append = FALSE,
-                  column = "user_annotator")
-```
 
 ## Data Acknowledgment
 
@@ -308,7 +196,7 @@ When using CRANT data, please acknowledge it in accordance with the [CRANT commu
 
 If you use this package, please cite:
 
-1. The upcoming CRANTb paper (TBD)
+1. The upcoming CRANT paper (TBD)
 2. The natverse paper: [Bates et al. 2020](https://elifesciences.org/articles/53350)
 3. This R package:
 
@@ -320,9 +208,9 @@ citation(package = "crantr")
 
 ## Acknowledgements
 
-- CRANTb data set: Lindsey E. Lopes and David G.C. Hildebrand prepared the clonal raider ant brain sample. The EM dataset was collected at Harvard Medical School in the [laboratory of Wei-Chung Allen Lee](https://www.lee.hms.harvard.edu/), by Wangchu Xiang, Mohd Mazri, and Lindsey E. Lopes.
+- CRANT data set: Collected at Harvard Medical School in the laboratory of Wei-Chung Allen Lee, by Wangchu Xiang and Lindsey Lopes.
 - Segmentation and synapse prediction: Built by [Zetta.ai](https://zetta.ai/).
-- Neuron reconstruction: Hosted and supported by the laboratory of Wei-Chung Allen Lee and the [Laboratory of Social Evolution and Behavior](https://www.rockefeller.edu/our-scientists/heads-of-laboratories/988-daniel-kronauer/) at The Rockefeller University.
+- Neuron reconstruction: Hosted and supported by the laboratory of Wei-Chung Allen Lee and the Kronauer Laboratory at the Rockerfeller Institute.
 - R package: Initialized using the [fancr](https://github.com/flyconnectome/fancr) package developed by Greg Jefferis at the MRC Laboratory of Molecular Biology, Cambridge, UK.
 - Development: Alexander S. Bates worked on this R package while in the laboratory of Rachel Wilson at Harvard Medical School.
 

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