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AnanseSeurat

Single cell ANANSE Gene-regulatory-network analysis from Seurat objects

https://github.com/jgasmits/ananseseurat

Science Score: 26.0%

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    CITATION.cff file
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    Low similarity (14.9%) to scientific vocabulary

Keywords

grn-analysis r seurat-objects single-cell single-cell-atac-seq single-cell-rna-seq
Last synced: 6 months ago · JSON representation

Repository

Single cell ANANSE Gene-regulatory-network analysis from Seurat objects

Basic Info
  • Host: GitHub
  • Owner: JGASmits
  • License: apache-2.0
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 620 KB
Statistics
  • Stars: 8
  • Watchers: 1
  • Forks: 3
  • Open Issues: 2
  • Releases: 4
Topics
grn-analysis r seurat-objects single-cell single-cell-atac-seq single-cell-rna-seq
Created over 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme Changelog License

README.Rmd 

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/",
  out.width = "100%"
)
```
# `AnanseSeurat` package 


[![R-CMD-check](https://github.com/JGASmits/AnanseSeurat/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/JGASmits/AnanseSeurat/actions/workflows/R-CMD-check.yaml)
[![codecov](https://codecov.io/github/JGASmits/AnanseSeurat/branch/main/graph/badge.svg?token=0XKWAD0KJ7)](https://codecov.io/github/JGASmits/AnanseSeurat)
[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/AnanseSeurat)](https://cran.r-project.org/package=AnanseSeurat)


The `AnanseSeurat` package takes pre-processed clustered single cell objects of scRNAseq and scATACseq or a multiome combination, and generates files for gene regulatory network (GRN) analysis.


## Installation

 `AnanseSeurat` can be installed using
```{r, eval=FALSE}
library(devtools) # Tools to Make Developing R Packages Easier # Tools to Make Developing R Packages Easier
Sys.unsetenv("GITHUB_PAT")
remotes::install_github("JGASmits/AnanseSeurat@main")
```

### Usage
```{r eval=FALSE}
library("AnanseSeurat")
rds_file <- './scANANSE/preprocessed_PDMC.Rds'
pbmc <- readRDS(rds_file)
```

Next you can output the data from your single cell object, the file format, config file and sample file are all ready to automate  GRN analysis using `anansnake`.
https://github.com/vanheeringen-lab/anansnake

```{r, eval=FALSE}
export_CPM_scANANSE(
  pbmc,
  min_cells = 25,
  output_dir = './scANANSE/analysis',
  cluster_id = 'predicted.id',
  RNA_count_assay = 'RNA'
)

export_ATAC_scANANSE(
  pbmc,
  min_cells = 25,
  output_dir = './scANANSE/analysis',
  cluster_id = 'predicted.id',
  ATAC_peak_assay = 'peaks'
)

# Specify additional contrasts:
contrasts <-  c('B-naive_B-memory',
                'B-memory_B-naive',
                'B-naive_CD14-Mono',
                'CD14-Mono_B-naive')

config_scANANSE(
  pbmc,
  min_cells = 25,
  output_dir = './scANANSE/analysis',
  cluster_id = 'predicted.id',
  additional_contrasts = contrasts
)

DEGS_scANANSE(
  pbmc,
  min_cells = 25,
  output_dir = './scANANSE/analysis',
  cluster_id = 'predicted.id',
  additional_contrasts = contrasts
)
```


### install and run anansnake 

Follow the instructions its respective github page, https://github.com/vanheeringen-lab/anansnake
After activating the conda environment, use the generated files to run GRN analysis using your single cell cluster data:

```{bash eval=FALSE}
anansnake \
--configfile scANANSE/analysis/config.yaml \
--resources mem_mb=48_000 --cores 12
```



### import ANANSE results back to your single cell object
After running Anansnake, you can import the TF influence scores back into your single cell object of choice
```{r eval=FALSE}
pbmc <- import_seurat_scANANSE(pbmc,
                               cluster_id = 'predicted.id',
                               anansnake_inf_dir = "./scANANSE/analysis/influence")
TF_influence <- per_cluster_df(pbmc,
                               cluster_id = 'predicted.id',
                               assay = 'influence')
```


### Thanks to:

* Julian A. Arts and his Pycharm equivalent of this package https://github.com/Arts-of-coding/AnanseScanpy 
* Siebren Frohlich and his anansnake implementation https://github.com/vanheeringen-lab/anansnake
* Rebecca R. Snabel for her implementation of the motif expression correlation analysis
* Branco Heuts for testing

# Credits
The hex sticker is generated using the [```hexSticker```](https://github.com/GuangchuangYu/hexSticker) package.

Owner

  • Name: Jos Smits
  • Login: JGASmits
  • Kind: user
  • Company: Radboud university

GitHub Events

Total
  • Watch event: 1
Last Year
  • Watch event: 1

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 102
  • Total Committers: 4
  • Avg Commits per committer: 25.5
  • Development Distribution Score (DDS): 0.137
Top Committers
Name Email Commits
JGASmits j****3@h****m 88
Rebecza r****l@h****m 10
Rebecca Snabel s****l@c****l 3
J Arts 7****g@u****m 1
Committer Domains (Top 20 + Academic)
cn106.science.ru.nl: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 9
  • Total pull requests: 26
  • Average time to close issues: 15 days
  • Average time to close pull requests: about 21 hours
  • Total issue authors: 4
  • Total pull request authors: 4
  • Average comments per issue: 1.33
  • Average comments per pull request: 0.19
  • Merged pull requests: 25
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • sylestiel (4)
  • Rebecza (2)
  • JGASmits (1)
  • saketkc (1)
Pull Request Authors
  • JGASmits (16)
  • Rebecza (8)
  • Arts-of-coding (1)
  • MichaelChirico (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 773 last-month
  • Total docker downloads: 48
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: AnanseSeurat

Construct ANANSE GRN-Analysis Seurat

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 773 Last month
  • Docker Downloads: 48
Rankings
Forks count: 17.8%
Stargazers count: 22.5%
Average: 27.1%
Dependent packages count: 29.8%
Downloads: 30.1%
Dependent repos count: 35.5%
Maintainers (1)
Jsmits@science.ru.nl
Last synced: 6 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/check-r-package v1 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
  • r-lib/actions/setup-r-dependencies v1 composite
DESCRIPTION cran
  • Seurat * imports
  • dplyr * imports
  • ggplot2 * imports
  • ggpubr * imports
  • magrittr * imports
  • patchwork * imports
  • png * imports
  • purrr * imports
  • rlang * imports
  • stringr * imports
  • utils * imports
.github/workflows/test-coverage.yaml actions
  • actions/checkout v3 composite
  • actions/upload-artifact v3 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite