https://github.com/natverse/neuprintr
R client utilities for interacting with the neuPrint connectome analysis service
https://github.com/natverse/neuprintr
connectomics neuroanatomy-toolbox neuroscience r
Last synced: 6 months ago
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R client utilities for interacting with the neuPrint connectome analysis service
- Host: GitHub
- URL: https://github.com/natverse/neuprintr
- Owner: natverse
- Created: 2019-03-19T11:22:52.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2025-10-01T06:13:25.000Z (10 months ago)
- Last Synced: 2025-10-01T08:23:47.151Z (10 months ago)
- Topics: connectomics, neuroanatomy-toolbox, neuroscience, r
- Language: R
- Homepage: http://natverse.org/neuprintr
- Size: 20.6 MB
- Stars: 4
- Watchers: 12
- Forks: 3
- Open Issues: 16
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
Awesome Lists containing this project
README
---
output:
md_document:
variant: gfm
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "",
fig.path = "README-"
)
```
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[](https://doi.org/10.5281/zenodo.3843544)
# neuprintr
The goal of *neuprintr* is to provide R client utilities for interacting with the neuPrint connectome analysis service. neuPrint is set of tools for loading and analysing connectome data into a Neo4j database.
You can find [neuprint](https://github.com/connectome-neuprint/neuPrint) on Github.
There is also a great python client available from Philipp Schlegel, [neuprint-python](https://github.com/schlegelp/neuprint-python) if that's your thing.
neuPrint is currently being used for connectome analysis in aid of neuronal reconstruction efforts at Janelia Research Campus. The main focus is analysis of the [hemibrain](https://www.janelia.org/project-team/flyem/hemibrain), densely reconstructed adult Drosophila brain dataset available at https://neuprint.janelia.org/.
For more information, have a look [here](https://neuprint.janelia.org/help).
Using this R package in concert with the [natverse](https://github.com/natverse/natverse) ecosystem is highly recommended.
## Tutorial
To help you get to grips with `neuprintr`, we have made a tutorial in classic presentation form. This tutorial uses data from the [Janelia Fly EM](https://www.janelia.org/project-team/flyem) team's [hemibrain](https://www.biorxiv.org/content/10.1101/2020.01.21.911859v1) project. You can also see the vignettes in this package for the same examples and more.
## Installation
```{r install, eval = FALSE}
# install
if (!require("devtools")) install.packages("devtools")
devtools::install_github("natverse/neuprintr")
# use
library(neuprintr)
```
## Authentication
In order to use *neuprintr* you will need to be able to login to a neuPrint server and be able to access it underlying Neo4j database.
You may need an authenticated accounted, or you may be able to register your `@gmail` address without an authentication process.
Navigate to a neuPrint website, e.g. https://neuprint.janelia.org, and hit 'login'. Sign in using an `@gmail` account.
If you have authentication/the server is public, you will now be able to see your access token by going to 'Account':
To make life easier, you can then edit your `.Renviron` file to contain information about the neuPrint server you want to speak with, your token and the dataset hosted by that server, that you want to read. A convenient way to do this is to do
```{r, eval=FALSE}
usethis::edit_r_environ()
```
and then edit the file that pops up, adding a section like
```{r, eval=FALSE}
neuprint_server="https://neuprint.janelia.org"
# nb this token is a dummy
neuprint_token="asBatEsiOIJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImIsImxldmVsIjoicmVhZHdyaXRlIiwiaW1hZ2UtdXJsIjoiaHR0cHM7Ly9saDQuZ29vZ2xldXNlcmNvbnRlbnQuY29tLy1QeFVrTFZtbHdmcy9BQUFBQUFBQUFBDD9BQUFBQUFBQUFBQS9BQ0hpM3JleFZMeEI4Nl9FT1asb0dyMnV0QjJBcFJSZlI6MTczMjc1MjU2HH0.jhh1nMDBPl5A1HYKcszXM518NZeAhZG9jKy3hzVOWEU"
```
Make sure you have a blank line at the end of your `.Renviron` file. Note that
you can optionally specify a default dataset:
```{r, eval=FALSE}
neuprint_dataset = "hemibrain:v1.1"
```
if your neuPrint server has more than one dataset. For further information
about neuprintr login, see the help for `neuprint_login()`.
Finally you can also login on the command line once per session, like so:
```{r login2, eval = FALSE}
conn = neuprint_login(server= "https://neuprint.janelia.org/",
token= "asBatEsiOIJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImIsImxldmVsIjoicmVhZHdyaXRlIiwiaW1hZ2UtdXJsIjoiaHR0cHM7Ly9saDQuZ29vZ2xldXNlcmNvbnRlbnQuY29tLy1QeFVrTFZtbHdmcy9BQUFBQUFBQUFBDD9BQUFBQUFBQUFBQS9BQ0hpM3JleFZMeEI4Nl9FT1asb0dyMnV0QjJBcFJSZlI6MTczMjc1MjU2HH0.jhh1nMDBPl5A1HYKcszXM518NZeAhZG9jKy3hzVOWEU")
```
This is also the approach that you would take if you were working with more than
two neuPrint servers.
## Example
Now we can have a look at what is available
```{r example, eval = FALSE}
# What data sets are available?
neuprint_datasets()
# What's the underlying database
neuprint_database()
# What are the regions of interrst in your default datasest (specified in R.environ, see ?neuprint_login)
neuprint_ROIs()
```
Use the client to request data from neuprint. The `neuprint_fetch_custom` method will run an arbitrary cypher query against the database. For information about the neuprint data model, see the neuprint explorer web help: https://neuprint.janelia.org/help.
Some cyphers and other API endpoints have been explored by this package. Have a look a the functions, for example, that give you neuron skeletons, synapse locations, connectivity matrices, etc.
```{r example2, eval = FALSE}
?neuprint_search
?neuprint_get_adjacency_matrix
?neuprint_ROI_connectivity
?neuprint_get_synapses
?neuprint_read_neurons
```
## Example data
* HemiBrain (hemibrain:v1.0) : from ["A Connectome of the Adult Drosophila Central Brain"](https://www.biorxiv.org/content/10.1101/2020.01.21.911859v1) (Xu, et al. 2020)
* mushroombody (mb6) : from ["A connectome of a learning and memory center in the adult Drosophila brain"](https://elifesciences.org/articles/26975) (Takemura, et al. 2017)
* medulla7column (fib25) : from ["Synaptic circuits and their variations within different columns in the visual system of Drosophila"](https://www.pnas.org/content/112/44/13711) (Takemura, et al. 2015)
## Acknowledging the data and tools
neuPrint comprises a set of tools for loading and analyzing connectome data into a Neo4j database. Analyze and explore connectome data stored in Neo4j using the neuPrint ecosystem: [neuPrintHTTP](https://github.com/connectome-neuprint/neuPrintHTTP), [neuPrintExplorer](https://github.com/connectome-neuprint/neuPrintExplorer), [Python API](https://github.com/connectome-neuprint/neuprint-python).
This package was created by [Alexander Shakeel Bates](https://scholar.google.com/citations?user=BOVTiXIAAAAJ&hl=en) and [Gregory Jefferis](https://en.wikipedia.org/wiki/Gregory_Jefferis) with Romain [Franconville](https://scholar.google.com/citations?user=I7yBLlsAAAAJ&hl=en)
now providing key contributions. You can cite a specific version of this package as:
```{r citation, eval = TRUE}
citation(package = "neuprintr")
```
however we would appreciate if you would cite the *natverse* journal article in which *neuprintr* was first introduced.
You can get full citation details for that as follows:
```{r citation2, eval = TRUE}
citation(package = "natverse")
```