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bbknnr

Use batch balanced KNN (BBKNN) in R

https://github.com/ycli1995/bbknnr

Science Score: 26.0%

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    Low similarity (12.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Use batch balanced KNN (BBKNN) in R

Basic Info
  • Host: GitHub
  • Owner: ycli1995
  • License: other
  • Language: R
  • Default Branch: main
  • Size: 4.26 MB
Statistics
  • Stars: 11
  • Watchers: 1
  • Forks: 5
  • Open Issues: 5
  • Releases: 0
Created about 4 years ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

bbknnR

Use batch balanced KNN (BBKNN) in R

Introduction

BBKNN is a fast and intuitive batch effect removal tool for single-cell data. It is originally used in the scanpy workflow, and now can be used with Seurat seamlessly.

System requirements

bbknnR has been tested on R versions >= 4.1. Please consult the DESCRIPTION file for more details on required R packages. bbknnR has been tested on Linux platforms

To use the full features of bbknnR, you also need to install the bbknn python package: pip install bbknn

Installation

bbknnR has been released to CRAN: install.packages("bbknnR") or can be installed from github: devtools::install_github("ycli1995/bbknnR")

Quick start

library(bbknnR) library(Seurat) data("panc8_small") panc8_small <- RunBBKNN(panc8_small, batch_key = "tech")

Release

2.0.1

  • Add k_build_nndescent = 30 parameter to match the implementation of python bbknn.

2.0.0

  • Remove reticulate dependency. Now use kNN algorithms provided by RcppAnnoy and rnndescent
  • Add return.umap.model for RunBBKNN.Seurat
  • Improvements for testthat

1.1.0

  • Compatibility with Seurat v5
  • Improvements for documentation and verbose.

1.0.2

  • Explicit import of get_dummies.() from tidytable
  • Fix a bug when pass only one batch_key to RidgeRegression()

1.0.1

  • Import public function similarity_graph() from uwot==0.1.14 in compute_connectivities_umap() to follow the CRAN policy

1.0.0

  • Initially released to CRAN

Citation

Please cite this implementation R in if you use it: Yuchen Li (2022). bbknnR: Use batch balanced KNN (BBKNN) in R. package version 0.1.0 https://github.com/ycli1995/bbknnR

Please also cite the original publication of this algorithm. Polanski, Krzysztof, et al. "BBKNN: fast batch alignment of single cell transcriptomes." Bioinformatics 36.3 (2020): 964-965.

Owner

  • Name: Yuchen Li
  • Login: ycli1995
  • Kind: user

GitHub Events

Total
  • Issues event: 2
  • Watch event: 5
  • Issue comment event: 3
  • Push event: 2
  • Fork event: 1
Last Year
  • Issues event: 2
  • Watch event: 5
  • Issue comment event: 3
  • Push event: 2
  • Fork event: 1

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 8
  • Total pull requests: 3
  • Average time to close issues: 25 days
  • Average time to close pull requests: 25 days
  • Total issue authors: 8
  • Total pull request authors: 1
  • Average comments per issue: 1.5
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • MingcanTang (1)
  • parkjooyoung99 (1)
  • Famingzhao (1)
  • WuRAFY (1)
  • edroaldo (1)
  • jlmelville (1)
  • Laraine-Z (1)
  • saketkc (1)
Pull Request Authors
  • markfairbanks (3)
Top Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 447 last-month
  • Total docker downloads: 48
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 7
  • Total maintainers: 1
cran.r-project.org: bbknnR

Perform Batch Balanced KNN in R

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 447 Last month
  • Docker Downloads: 48
Rankings
Forks count: 17.8%
Stargazers count: 24.2%
Dependent packages count: 29.8%
Average: 33.4%
Dependent repos count: 35.5%
Downloads: 60.0%
Maintainers (1)
ycli1995@outlook.com
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 4.1.0 depends
  • methods * depends
  • utils * depends
  • Matrix * imports
  • Rcpp * imports
  • RcppAnnoy * imports
  • Rtsne * imports
  • Seurat * imports
  • SeuratObject * imports
  • dplyr * imports
  • glmnet * imports
  • reticulate * imports
  • tidytable * imports
  • uwot >= 0.1.14 imports
  • knitr * suggests
  • patchwork * suggests
  • rmarkdown * suggests
  • testthat >= 3.0.0 suggests