MOMIA (or Mycobacteria Optimized Microscopy Image Analysis) is a python based image analysis toolkit optimized for dealing with mycobacterial cells. Given a single or a set of fluorescent microscopic image(s), MOMIA renders accurate object segmentation and graphical representation of fluroescent or morphological profiles at both the single cell level and the populational level. MOMIA was developed to analyze a M. smegmatis fluorsecent protein tagging library (Mycobacterial Systems Resource, Dendra, or MSR-Dendra) which accounts for over 1,000 highly conserved mycobacterial genes. You may find the MSR-Dendra dataset (along with many other amazing mycobacterial resources) on this website.
A light-weight, Non-negative matrix factorization (NMF) based post-segmentation data analysis tool, GEMATRIA (Graph Embedded, Multi-Attribute Temporal Reconstruction of Intracellular protein Allocation) is also included in this deposit. GEMATRIA seeks to infer visually intuitive features from high-throughput fluorescent-protein imaging datasets. These protein localization features, in combination with a cell length based binning approach, enables the users to approximate and quantitate the spatio-temporal dynamics of proteins of interest.
To install MOMIA and GEMATRIA from the Python Package index (PyPi) , make sure you have pip installed, then run:
$ pip install momia
Users can import MOMIA and GEMATRIA just like other python packages in any IDE by running
import MOMIA as mo
or:
import GEMATRIA as gem
Tutorials for MOMIA and GEMATRIA are included in the folder /notebooks
Please feel free to contact me if you have any issues (almost guaranteed) using MOMIA or GEMATRIA.