Figure 2.

eLSA pipeline. Users start with raw data (matrices of time series) as input and specify their requirements as parameters. The LSA tools subsequently F-transform and normalize the raw data and calculate Local Similarity (LS) scores and Pearson’s Correlation Coefficients. The tools then assess the statistical significance (P-values) of these correlation statistics using the permutation test and filter out insignificant results. Finally, the tools construct a partially directed association network from the significant associations.