## Inference of Transcription Factor Concentrations and Regulatory IntensitiesThis page describes examples of how to use the Dynamical Model for Variational Inference of Protein Concentration and Regulatory Intensities detailed in . The code is available for download here.## Release InformationCurrent release is 0.11. Release 0.11 contains a bug fix for file chipVarEstepCMu.m Release 0.1 is the first release associated with the paper, containing scripts for recreating the results given. The toolboxes required to run the code are listed below.
Finally you will also need the NETLAB toolbox in your path. ## Results in the PaperThe main scripts are`demTuVar` and `demSpellmanVar`
which run the code on the metabolic and cell cycle data sets. Also of
interest may be the script `demFakeVar` which
runs the code on artificial data. `demTuVar` and `demSpellmanVar`
invoke the functions `chipVarEMmu` and `chipVarEM`
respectively
which compute the posterior estimates of the latent variables by
maximising the
variational lower bound on the likelihood. The functions used are
different as there
is no need to estimate the baseline expression level for cDNA array
data such as the
cell cycle data set. The scripts output a variable model, containing
the parameter
values which maximise the likelihood, and expectationsB (posterior
expectations of
the regulatory intensities) and expectationsC, posterior expectations
of the protein
concentration profiles. The function `chipVarEMmu` also
outputs a variable
expectationsMu containing posterior statistics for the distribution of
the baseline
expression levels.
The variable expectationsC has four fields: .entropy, a number
contatining the posterior
entropy of the approximating distribution, .c, a matrix with as many
rows as transcription factors and as many columns as time points, .ccT,
a 3D array containing
the correlations among transcription factors at each time point, and
.cAltc, a 3D array
containing correlations among transcription factors at consecutive time
points. By specialising the transcription factor index one can obtain
plots of the transcription
factor protein concentrations with errorbars. An example is show below
for the transcription factor ACE2 during the cell cycle.
Inferred protein concentration profile for the transcription factor ACE2 during the yeast cell cycle. `expectationsB.errorbars`
contains the associated error bars. By specifying to a transcription
factor, we can
obtain a distribution of the significance levels of its regulatory
intensities. An example of this is shown below for the transcription
factor ACE2 during the cell cycle.
Significance of the regulatory intensities for the transcription factor ACE2 during the yeast cell cycle. The plot shows the ratio between gene-specific regulatory intensities and the associated noise |