colocr
colocr performs co-localization analysis of fluorescence microscopy images to quantify spatial distribution and assess potential functional or physical associations between two proteins within cells.
Key Features:
- Image loading: Supports loading fluorescence microscopy images for downstream analysis.
- Region of interest (ROI) selection: Enables selection and specification of ROIs for targeted co-localization assessment.
- Co-localization metrics computation: Calculates quantitative co-localization metrics to evaluate protein co-distribution.
Scientific Applications:
- Protein co-localization analysis: Quantifies spatial overlap of two proteins within cellular compartments using microscopy data.
- Inference of functional or physical associations: Supports interpretation of potential protein–protein interactions and cellular mechanisms from co-distribution patterns.
Methodology:
Computational steps explicitly include loading fluorescence microscopy images, selecting regions of interest (ROIs), and computing co-localization metrics to quantify protein co-distribution.
Topics
Details
- License:
- GPL-3.0
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 7/31/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Ahmed M, Lai TH, Kim DR. colocr: an R package for conducting co-localization analysis on fluorescence microscopy images. PeerJ. 2019;7:e7255. doi:10.7717/peerj.7255. PMID:31309005. PMCID:PMC6612416.
DOI: 10.7717/peerj.7255
PMID: 31309005
PMCID: PMC6612416
Funding: - Ministry of Education Science and Technology: 2018R1D1A1B07043715
- Ministry of Science, ICT and Future Planning: NRF2015R1A5A2008833
Documentation
Downloads
- Source codeVersion: 0.1.0https://github.com/ropensci/colocr/archive/v0.1.0.zip
Links
Issue tracker
https://github.com/ropensci/colocr/issues