Derivation of over/under-represented TFBSs using an ensemble of statistical metrics.

Marina is an OS-independent GUI tool for computing TFBS abundance given two sets of promoter sequences. Marina performs such computations by harnessing 7 knowledge-discovery statistical metrics and the hypergeometric distribution so as to infer magnitude of TFBS over-representation. A standardization algorithm known as Iterative Proportional Fitting (IPF) enables "agreement" across these various metrics as to which TFBSs are the most over-represented and which are not.
In order to run Marina, a collection of TFBS models are required. Sample models are included.
Valid models are partitioned into two specific classes:

  1. Position Weight Matrices (PWM): Matrices which model nucleotide propensity of being part of a TFBS
  2. DNA motifs: Linear DNA sequences representative of a TFBS
For those interested in plant TFBS analyses, several databases exist which contain the above models: TRANSFAC, AthaMap, AGRIS, JASPAR

Marina works with TFBS models be-it PWMs and/or DNA motif as long as they follow their respective schema outlined in the documentation.
This tool is designed for ease-of-use and interpretation; to aide the investigator deduce over/under-represented TFBSs and magnitude of.

Download and Release Information.

Originally, Marina was built using Python and the PyQt4 GUI library (see Marina 0.67). We re-built Marina from the ground-up using Java and JavaFX (a GUI library now part of the Java7+ language). We encourage usage of this latest Java build over prior Python builds as it provides increased UI interaction, runtime performance, various bug-fixes and improved threading support.

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