SCMD

SCMD enables quantitative analysis of Saccharomyces cerevisiae cell morphology from micrographs to support identification of genes and perturbations that affect cell shape.

Key Features:

• Automated Image Processing: Automatically extracts yeast cells from large collections of micrographs using specialized image-processing software.
• Quantitative Morphological Analysis: Measures approximately 500 morphological parameters, including cell size, roundness, bud neck position angle, nuclear DNA localization, actin patch morphology, and fits ellipses to cell outlines to capture mother and daughter cell shapes.
• Large-Scale Data Collection: Contains datasets of processed images including over 960,609 cells from 52,988 micrographs of 2,531 mutants (Publication 1) and 1,899,247 cell images from 91,71 micrographs of 4,782 disruptants (Publication 2).
• Data Mining and Visualization Tools: Provides software for visualizing parameter value distributions and identifying combinations of multiple parameters that discriminate between mutant groups associated with specific functions.
• Similarity Search Functionality: Ranks mutants by average morphological parameters to enable searches for mutants with similar morphological traits.

Scientific Applications:

• Global morphology regulation: Quantitative comparison across mutants to study global regulation of Saccharomyces cerevisiae cell morphology.
• Gene-function identification: Correlating morphological signatures with mutants to identify genes and perturbations relevant to specific biological processes affecting cell shape.
• Genome-wide screening: Supporting genome-wide screening studies to uncover genetic determinants of morphological traits using large-scale quantitative morphology datasets.

Methodology:

High-throughput image processing automatically extracts cells from micrographs, fits ellipses to cell outlines, quantifies approximately 500 morphological parameters, and integrates visualization and data-mining tools for analysis.