Resolution:
## Figure 3.
How PARma works. PARma is an iterative algorithm, which repeatedly executes three steps: based on
a current model of the PAR-CLIP characteristics (left; see also Figure 6), scores
are computed for each position in each cluster, which express the likelihood that
the cluster is explained by the activity of the k-mer at this position (top right;
see also Figure 7). These scores are fed into kmerExplain as prior probabilities,
which then estimates k-mer activity probabilities using an EM algorithm (bottom).
These k-mer activities in conjunction with data from the PAR-CLIP experiment (T to
C conversions and RNase cleavage sites) are used to estimate the parameters of the
PAR-CLIP model. We start this procedure by running kmerExplain on uniform scores and
end it as soon as the model converges. EM, expectation maximization.
Erhard |