CFQuant-automatic
CFQuant-automatic quantifies luminescent and fluorescent halos around cell colonies in high-throughput images to provide quantitative measurements for colony luminescence assays.
Key Features:
- Automatic Identification and Quantification: Automatically identifies cell colonies and their associated luminescent or fluorescent halos in images despite biological noise.
- Shape-Based Analysis: Leverages the expected shape of luminescence halos to improve detection and measurement accuracy.
- Quantitative Data Output: Produces detailed quantitative measurements of features related to colonies and their luminescent halos.
- High-throughput Image Analysis and Validation: Performs high-throughput image analysis and was validated by correlation with known protein expression levels (R = 0.85).
Scientific Applications:
- Colony luminescence assays: Quantifies luminescence and fluorescence levels around colonies for reporter-based assays in microbiological research.
- Comparative trait analysis: Enables comparison of luminescence-derived traits across different strains or treatments.
Methodology:
High-throughput image analysis that identifies colonies and luminescent/fluorescent halos using shape-based criteria, with validation by correlation to protein expression levels (R = 0.85).
Topics
Details
- License:
- Unlicense
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- desktop application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- MATLAB
- Added:
- 5/27/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Dafni E, Weiner I, Shahar N, Tuller T, Yacoby I. Image-Processing Software for High-Throughput Quantification of Colony Luminescence. mSphere. 2019;4(1). doi:10.1128/msphere.00676-18. PMID:30602526. PMCID:PMC6315083.
PMID: 30602526
PMCID: PMC6315083
Funding: - United States-Israel Binational Science Foundation: 2016666
- Israel Science Foundation: 1646/16, 2185/17
Documentation
Downloads
- Source codehttps://github.com/eyaldaf/CFQuant