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We therefore define a correspondence set C ab of size Q as the list of correspondences c q found between FP a and FP b which possess the highest correspondence score.
For a given locus and PPM motif of width m, a correspondence score was calculated using position weight matrices (PWMs), which were calculated from PPM nucleotide probabilities (p) and nucleotide background frequencies (f), as described in the following equation [55].
AC: Audic-Claverie; CS: Correspondence Score; DABG: Detection Above Background; MPNS: Massively Parallel Nucleotide Sequencing; PSR: Probe Selection Region.
At each combination of expression level and DABG threshold, we calculated a correspondence score (CS; see Methods).
To measure the correspondence between a given cluster and a specific annotation, we define the notion of a correspondence score (CS).
> -wrap-foot> We implemented in ProtoBug Database and Webserver the notion of a correspondence score (CS) to assess the purity and coverage.
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If λ is larger than a predefined threshold λ t, we do not apply PCT to the node correspondence scores.
The resulting node correspondence scores are then used to predict the maximum expected accuracy (MEA) alignment of the given networks.
Finally, in the proposed method, we used λ t = 0.7 to determine whether or not to apply PCT to the estimated node correspondence scores.
First, in order to improve the reliability of the node correspondence scores, we selectively apply the probabilistic consistent transformation (PCT) defined in [ 12].
For example, SMETANA [ 12] tries to estimate probabilistic node correspondence scores using a semi-Markov random walk model, and then uses the estimated scores to predict the maximum expected accuracy (MEA) alignment of the given networks.
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