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returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["connectomics","neuroanatomy-toolbox","neuroscience","r"],"created_at":"2026-01-20T05:38:07.027Z","updated_at":"2026-02-17T17:11:31.249Z","avatar_url":"https://github.com/natverse.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003c!-- badges: start --\u003e\n[![natverse](https://img.shields.io/badge/natverse-Part%20of%20the%20natverse-a241b6)](https://natverse.github.io)\n[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)\n[![Release Version](https://img.shields.io/github/release/natverse/fafbseg.svg)](https://github.com/natverse/fafbseg/releases/latest) \n[![Docs](https://img.shields.io/badge/docs-100%25-brightgreen.svg)](https://natverse.github.io/fafbseg/reference/)\n[![R-CMD-check](https://github.com/natverse/fafbseg/workflows/R-CMD-check/badge.svg?branch=master)](https://github.com/natverse/fafbseg/actions)\n[![Codecov test coverage](https://codecov.io/gh/natverse/fafbseg/branch/master/graph/badge.svg)](https://app.codecov.io/gh/natverse/fafbseg?branch=master)\n\u003c!-- badges: end --\u003e\n\n# fafbseg\n\nThe goal of fafbseg is to provide support for analysis of segmented EM data,\nfocussed on the [full adult female brain (FAFB) dataset](http://temca2data.org/).\n\nAlthough there is support for a range of data sources and services, at this point\nthe principal target is the [FlyWire](https://flywire.ai/) automated segmentation.\nLegacy support also exists for the [Google brain](http://fafb-ffn1.storage.googleapis.com/landing.html) automatic\nsegmentation of FAFB data.\n\n**fafbseg** is integrated with the [NeuroAnatomy Toolbox](https://github.com/natverse/nat)\nsuite (aka [natverse](http://natverse.org)) including [elmr](https://github.com/natverse/elmr) and [catmaid](https://github.com/natverse/rcatmaid).\n\n**fafbseg** is also one building block for the [coconatfly](https://natverse.org/coconatfly/)\nwhich provides a unified and simplified interface to a range of Drosophila\nconnectome datasets. We actually recommend [coconatfly](https://natverse.org/coconatfly/)\nas a good place to start for most users since it provides convenient access\nto specific FlyWire data releases as well as powerful cross-connectome analyses\nwhile requiring minimal configuration. See\nhttps://natverse.org/coconatfly/articles/getting-started.html for details.\n\n## Installation\n\nAssuming you want to use the production (in progress) version of the FlyWire dataset\nor to access lower level functionality, then fafbseg is the way to go. You will\nneed to install the package and then configure your environment including\nrecording your authorisation token and likely downloading canned data releases.\n\n### Package installation\n\nWe recommend installing fafbseg from GitHub using the [natmanager package](http://natverse.org/natmanager/):\n\n``` r\n# install natmanager if required\nif (!requireNamespace(\"natmanager\")) install.packages(\"natmanager\")\nnatmanager::install(pkgs=\"fafbseg\")\n```\n\n### FlyWire setup\n\nBasic steps for setting up to access FlyWire data:\n\n``` r\nlibrary(fafbseg)\n# record your authorisation token\nflywire_set_token()\n# install python tools required for some functionality\nsimple_python()\n# fetch canned connectivity *and* cell type data \ndownload_flywire_release_data()\n```\nnote that at the time of writing (Dec 2023) `download_flywire_release_data()` \ntargets materialisation 783 of the FlyWire dataset, fetching both annotations and\nconnectivity information.\n\n## Use\n\nDetailed examples will follow in additional vignettes, but as a first motivation,\nthis is how to do a connectivity query using precomputed data.\n``` r\nlibrary(fafbseg)\ndl4df=flytable_meta('DL4.*')\ndl4df\n\ndl4out \u003c- flywire_partner_summary2(dl4df, partners = 'out', threshold = 3)\ndl4out\n```\n## Acknowledgements\n\nThe fafbseg package enables access to a number of published and many pre-publication \nresources. We hope that this will accelerate your science but we **strongly**\nrequest that you ensure that you acknowledge both the authors of this package\nand the original data sources to ensure that we and they can justify this free\nsharing of code and data.\n\nFor use of the proofread and annotated FlyWire dataset, please co-cite:\n\n* [Dorkenwald et al 2023](https://doi.org/10.1101/2023.06.27.546656)\n* [Schlegel et al. 2023](https://doi.org/10.1101/2023.06.27.546055)\n\nTo acknowledge specific FAFB resources:\n\n* For the FAFB dataset, [Zheng et al Cell 2018](https://www.cell.com/cell/fulltext/S0092-8674(18)30787-6)\n* For the FFN1 autosegmentation, [Li et al bioRxiv 2019](https://www.biorxiv.org/content/10.1101/605634v3)\n* For the FlyWire autosegmentation, [Dorkenwald et al Nat Meth 2022](https:// https://doi.org/10.1038/s41592-021-01330-0) and https://flywire.ai\n* For the Buhmann synaptic connection autosegmentation, [Buhmann et al Nat Meth 2021](https://doi.org/10.1038/s41592-021-01183-7)\n  * if using the `cleft_score` metric please also cite [Heinrich et al 2018](https://link.springer.com/chapter/10.1007%2F978-3-030-00934-2_36) \n* For the neurotransmitter prediction, [Eckstein et al. 2023 bioRxiv](https://www.biorxiv.org/content/10.1101/2020.06.12.148775)\n\nFlyWire coordinate transforms and synapse predictions make use of infrastructure\ncontributed by Davi Bock, Gregory Jefferis, Philipp Schlegel and Eric Perlman,\nsupported by NIH BRAIN Initiative (grant 1RF1MH120679-01); additional work\nincluding assembling ground truth data was also supported by Wellcome trust\n(203261/Z/16/Z). \n\nFor the fafbseg package itself, please include a reference to the github page\nin your methods section as well as a citation to [Bates et al eLife 2020](https://doi.org/10.7554/eLife.53350) along with the statement:\n\n\u003e Development of the natverse including the fafbseg package has been supported \nby the NIH BRAIN Initiative (grant 1RF1MH120679-01), NSF/MRC Neuronex2 (NSF 2014862/MC_EX_MR/T046279/1) and core funding from the Medical Research Council (MC_U105188491).\n\n**Thank you!**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnatverse%2Ffafbseg","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnatverse%2Ffafbseg","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnatverse%2Ffafbseg/lists"}