Data

Tools

Indexes

Applications

Experiments

Open Source Science

SEraster

Spatial Experiments raster - a rasterization preprocessing framework for scalable spatial omics data analysis

https://github.com/jefworks-lab/seraster

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
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 4 committers (25.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (14.6%) to scientific vocabulary

Keywords

rstats spatial-analysis spatial-data-analysis spatial-omics spatial-transcriptomics
Last synced: 6 months ago · JSON representation

Repository

Spatial Experiments raster - a rasterization preprocessing framework for scalable spatial omics data analysis

Basic Info
Statistics
  • Stars: 18
  • Watchers: 1
  • Forks: 5
  • Open Issues: 1
  • Releases: 0
Topics
rstats spatial-analysis spatial-data-analysis spatial-omics spatial-transcriptomics
Created over 2 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog

README.md

Spatial Experiments raster (SEraster)

SEraster is a rasterization preprocessing framework that aggregates cellular information into spatial pixels to reduce resource requirements for spatial omics data analysis. This is the SEraster R documentation website. Questions, suggestions, or problems should be submitted as GitHub issues.

Overview

SEraster reduces the number of spatial points in spatial omics datasets for downstream analysis through a process of rasterization where single cells' gene expression or cell-type labels are aggregated into equally sized pixels based on a user-defined resolution. Here, we refer to a particular resolution of rasterization by the side length of the pixel such that finer resolution indicates smaller pixel size and coarser resolution indicates larger pixel size.

Installation

To install SEraster using Bioconductor, start R (version "4.5.0") and run:

```r if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("SEraster") ```

See Bioconductor for more details.

The latest development version can also be installed from GitHub using remotes:

r require(remotes) remotes::install_github('JEFworks-Lab/SEraster')

In addition, SEraster is also compatible with SeuratObject through SeuratWrappers. SeuratWrappers implementation can be installed using remotes:

r require(remotes) remotes::install_github('satijalab/seurat-wrappers@SEraster')

Documentation and tutorial for the SeuratWrappers implementation can be found in the SEraster branch of the SeuratWrappers GitHub repository.

Tutorials

Introduction:

Citation

Our manuscript describing SEraster is available on Bioinformatics:

Gohta Aihara, Kalen Clifton, Mayling Chen, Zhuoyan Li, Lyla Atta, Brendan F Miller, Rahul Satija, John W Hickey, Jean Fan, SEraster: a rasterization preprocessing framework for scalable spatial omics data analysis, Bioinformatics, Volume 40, Issue 7, July 2024, btae412, https://doi.org/10.1093/bioinformatics/btae412

Owner

  • Name: JEFworks Lab
  • Login: JEFworks-Lab
  • Kind: organization

JEFworks Lab at Johns Hopkins University

GitHub Events

Total
  • Watch event: 2
  • Push event: 8
  • Pull request event: 2
  • Fork event: 1
Last Year
  • Watch event: 2
  • Push event: 8
  • Pull request event: 2
  • Fork event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 50
  • Total Committers: 4
  • Avg Commits per committer: 12.5
  • Development Distribution Score (DDS): 0.28
Past Year
  • Commits: 50
  • Committers: 4
  • Avg Commits per committer: 12.5
  • Development Distribution Score (DDS): 0.28
Top Committers
Name Email Commits
Gohta Aihara g****a@g****m 36
JEFworks j****n@j****u 8
GohtaAihara 3****a 4
LylaAtta123 l****a@L****l 2
Committer Domains (Top 20 + Academic)
jhu.edu: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 1
  • Total pull requests: 12
  • Average time to close issues: N/A
  • Average time to close pull requests: about 7 hours
  • Total issue authors: 1
  • Total pull request authors: 3
  • Average comments per issue: 3.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 12
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 5 minutes
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • lambdamoses (1)
Pull Request Authors
  • GohtaAihara (16)
  • LylaAtta123 (3)
  • mayling54 (2)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 1,407 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
bioconductor.org: SEraster

Rasterization Preprocessing Framework for Scalable Spatial Omics Data Analysis

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 1,407 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 30.3%
Average: 41.3%
Downloads: 93.7%
Maintainers (1)
gohta.aihara@gmail.com
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 2.10 depends
  • testthat >= 3.0.0 suggests