https://github.com/alleninstitute/cell_type_mapper

Repository for storing prototype functionality implementations for the BKP

https://github.com/alleninstitute/cell_type_mapper

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.5%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Repository for storing prototype functionality implementations for the BKP

Basic Info
  • Host: GitHub
  • Owner: AllenInstitute
  • License: other
  • Language: Python
  • Default Branch: main
  • Size: 38.7 MB
Statistics
  • Stars: 33
  • Watchers: 6
  • Forks: 7
  • Open Issues: 8
  • Releases: 0
Created over 3 years ago · Last pushed 10 months ago
Metadata Files
Readme Contributing License

README.md

Cell Type Mapper

Overview

This code provides a python package for mapping single sell RNA sequencing data onto a cell type taxonomy such as that provided by the Allen Institute for Brain Science.

Installation

To install this library, clone the repository, then (ideally from a clean python environment)

  • Run pip install -e . from the root directory of this repository to install this package itself.

This package has been tested extensively with python 3.9. We have no reason to believe that it will not also run with python 3.8 and 3.10.

Common use cases

In addition to the documentation referenced below, we provide several Jupyter notebooks detailing common use cases for this code.

Submitting data to online MapMyCells tool

The code in this repository provides the backend for the Allen Institute's online MapMyCells tool. This notebook walks the user through the process of downloading actual data, formatting it to be submitted to MapMyCells, and then downloading and interpreting the results. You may also want to consult this page for detailed documentation of the output produced by the mapping code.

Mapping to Allen Institute taxonomies on your own machine

If you want to run the code on your own machine, but still want to map to the taxonomies supported by the on-line MapMyCells tool, consult this page and Section 8 of this Jupyter notebook.

Mapping to a user-defined taxonomy

This Jupyter notebook walks the user through the process of creating a new taxonomy from cartoon data (generated by the notebook) and mapping unlabeled data to that taxonomy.

Creating and mapping to a taxonomy defined from a subset of the Allen Institute's data

This Jupyter notebook walks the user through the process of downloading a subset of the Allen Institute's Whole Mouse Brain data using the abcatlasaccess tool, creating a taxonomy based solely on that subset of the data, and mapping data to that new taxonomy.

Detailed documentation

The recommended workflow for running this code is here.

Documentation of the output produced by this code can be found here.

Level of support

We are providing this tool to the community and any and all who want to use it. Issues and pull requests are welcome, however, this code is also intended as part of the backend for the Allen Institute Brain Knowledge Platform. As such, issues and pull requests may be declined if they interfere with the functionality required to support that service.

Owner

  • Name: Allen Institute
  • Login: AllenInstitute
  • Kind: organization
  • Location: Seattle, WA

Please visit http://alleninstitute.github.io/ for more information.

GitHub Events

Total
  • Issues event: 11
  • Watch event: 14
  • Delete event: 2
  • Issue comment event: 47
  • Push event: 237
  • Pull request event: 6
  • Fork event: 3
  • Create event: 35
Last Year
  • Issues event: 11
  • Watch event: 14
  • Delete event: 2
  • Issue comment event: 47
  • Push event: 237
  • Pull request event: 6
  • Fork event: 3
  • Create event: 35

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 1,897
  • Total Committers: 2
  • Avg Commits per committer: 948.5
  • Development Distribution Score (DDS): 0.007
Past Year
  • Commits: 558
  • Committers: 1
  • Avg Commits per committer: 558.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
danielsf s****l@a****g 1,883
Carlos Caceres c****a@a****m 14
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 20
  • Total pull requests: 19
  • Average time to close issues: 3 months
  • Average time to close pull requests: 5 days
  • Total issue authors: 20
  • Total pull request authors: 3
  • Average comments per issue: 5.25
  • Average comments per pull request: 0.42
  • Merged pull requests: 9
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 11
  • Pull requests: 7
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 6 days
  • Issue authors: 11
  • Pull request authors: 1
  • Average comments per issue: 6.09
  • Average comments per pull request: 0.43
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • danielsf (2)
  • Winterwind (1)
  • mtvector (1)
  • inkarkapen (1)
  • berl (1)
  • mitsiask (1)
  • kulansam (1)
  • scseeman (1)
  • siennasage18 (1)
  • beyondpie (1)
  • zyll123 (1)
  • Xieeeee (1)
  • an-altosian (1)
  • KatMedMed (1)
  • mbatiuk (1)
Pull Request Authors
  • danielsf (13)
  • cacerca (7)
  • inkarkapen (1)
Top Labels
Issue Labels
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Dependencies

requirements.txt pypi
  • anndata *
  • argschema *
  • marshmallow ==3.12.2
  • matplotlib *
  • numpy *
  • pytest *
  • scipy *
  • zarr *
setup.py pypi