Overview of scoring procedure. (a) Schematic of the procedure used for generating interaction scores from jpeg images of double mutant yeast strain colonies. (b) A representative image of colonies of haploid double mutant yeast strains arising from the mating of one NAT-marked mutant strain to an array of 384 KAN-marked mutant strains, followed by sporulation and a selection process. (c) Median interaction scores as a function of the distance in kilobases between genes. All analysis shown is performed on data from Schuldiner et al. [5].

S scores are unbiased and quantitative. (a) Distribution of S scores for pairs of genes whose individual mutations give different growth phenotypes. The curves represent scores from pairs of genes whose individual mutations both yield slow growth phenotypes (blue circles), both yield growth phenotypes typical of our set of mutant strains (green triangles), and both yield relatively fast growth phenotypes (red squares). (b) Median interaction score on the second measurement (from an independent construction of strains) for pairs of genes with the indicated score on the first measurement. (c) Histograms of the observed colony size divided by the expected colony size for double mutant strains with S scores of approximately -3 (blue), -5 (green), -10 (red), and -20 (brown).

Quantitative genetic interaction scores allow for more precise functional characterization than binary scores do. (a) Different methods for scoring genetic interactions were compared by their propensity to yield high correlations between the profiles of pairs of genes that were assigned to the same functional category. For the S scores and for a binary score in which interactions were classified as either synthetic or noninteracting according to a threshold in the S score, gene pairs were sorted from highest correlation to lowest correlation. The curves show the cumulative number of gene pairs belonging to the same functional category versus the total number of gene pairs for the full S score (blue) and for the binary score (green). The red curve indicates the expected result if the gene pairs are sorted randomly. Inset is a bar graph showing integrations of the two curves over the full range of gene pairs after subtracting the background of the random expectation. The threshold for the binary score was chosen to maximize the integral shown in the inset. (b) The minimal cluster including the seven ALG genes and the four OST genes when clusters are made using hierarchal clustering with the correlation between the profiles of S scores used as the metric. (c) The minimal set of clusters containing the ALG and OST genes when the same clustering algorithm is performed using the binary scores rather than the S scores.

Effects of modifications in the S score (from a t-value) on score reproducibility. Each panel contains a scatter plot, in which each point represents two independent score measurements for a single pair of genes. All panels use the same raw data, but they differ in the scoring procedure used. The two scores come from the two possible pairings of antibiotic resistance markers with gene mutations. (a) Standard t-values in which colony sizes are normalized according to the mean colony size on the experimental plate. (b) Standard t-values using the normalization procedure described here. (c) Standard t-values with the normalizations described here and the removal of incorrect strains and experiments. (d) S scores without minimum bounds on variances. (e) Full S scores.

Estimating significance for S scores. (a) Schematic illustrating the strategy used to estimate the distribution of S scores arising from noninteracting gene pairs. The distribution of pairs of scores lying close to the 'Noise' axis (that is, pairs with an average score close to zero) were assumed to arise from noninteracting gene pairs. (b) Fit (with residuals shown below) of the distribution of scores lying close to the 'Noise' axis in (a) according to the model that individual S scores for noninteracting gene pairs follow a t-distribution (see Materials and methods for further explanation). (c) Plot of an estimate of the fraction of observations, as a function of averaged S score, that correspond to genuine genetic interactions.

A score to identify coherently acting gene pairs. (a) Plot of median averaged S score as a function of the correlation between the patterns of genetic interactions for pairs of genes. Reprinted from Schuldiner et al. [5] with permission from Elsevier 2005 (b) Scatter plot of averaged S score versus correlation in which each point represents one pair of genes. The plot is overlaid onto a color gradient indicating the COP score.