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In order to account for multiple hypotheses testing, we computed the False Discovery Rates (Benjamini and Hochberg, 1995).

To account for multiple hypothesis testing, we computed the q-value, or false discovery rate for a given p-value, by using 100 random resamplings of genes from the microarray experiment and testing each of these random resamplings for enrichment against each of the 1,338 chemical-gene sets.

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To correct for the multiple testing, we compute the q-value using the "qvalue" package for R software [ 56].

As a preliminary test, we computed the mean emotion and sentiment of content surrounding the 100 successful and 100 unsuccessful memes in our dataset.

As a second series of tests, we computed the average ratios of allele expression instead of the proportion of SNPs presenting ASGE.

For each test, we computed the standard deviation and coefficient of variation of the oscillation frequency and firing rate across the corresponding sliding windows (on average 161.99 windows for each test).

To gain insight into the potential effects of vaccination on the predictive value of a positive screening test, we computed the positive predictive values for detection of CIN2+ for women without HPV16 and 18.

Since the measurements are not normally distributed (P<10−15; Shapiro Wilk test), we computed the Wilcoxon rank sum test under the null hypothesis that the median difference between the two measurement sets is zero and the alternative hypothesis that the median half-life of the toxic transcription factors is less than that of the non-toxic ones.

Specifically, for each gene pair used in the test we computed the intron conservation ratio (ICR) between the two genes defined as follows (for more details see Methods): Figure 4 shows ICR histograms for pairs of genes falling in each of the four classes of agreement/disagreement between Inparanoid and local synteny.

In the test, we compute the maximum norm errors between the exact and the numerical solutions at the last time step by e(h,tau)=max_{1leq ileq N} biglvert u(x_{i},t_{M} -u_{i}^{M} -u_{i}rt, (11) where (u(x_{i},t_{M})) is the exact solution and (u_{i}^{M}) is the numerical solution with the mesh step sizes h and τ at the grid point ((x_{i},t_{M})).

For multiple testing corrections, we computed the false discovery rate (FDR) for each tag using statistical hypothesis testing involving Storey's method [15] (see Materials and Methods for detail).

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