Effect of pre-processing of pathway topologies on simulated data—Overexpression of single gene.

<p>Each point represents a single gene. Only genes common for pathway topologies from graphite package (+GPT) and method-specific pathway topologies (MSPT) are displayed. Points on diagonal represent genes with the same influence in +GPT and MSPT. Points below (above) diagonal represent genes with higher (lower) influence in MSPT.</p

Overview of the eight controlled experiments (Ex. 1-8) performed.

<p>Overview of the eight controlled experiments (Ex. 1-8) performed.</p

Proportion of differentially expressed pathways (DEPs) combined across all genes as function of the induced change.

<p>The proportion of differentially expressed pathways combined across all tested genes in the Non-small cell lung cancer pathway at different induced expression changes. Each line represents one method. Results were very similar for TopologyGSA and Clipper, and the respective lines are overlapping. Solid lines refer to pathway topology from graphite package (+GPT), dashed to pathway topology from graphite package without interactions (-GPT) and dotted to method-specific pathway topology (MSPT).</p

Proportion of significant target pathways in the Gene Overexpression Data Collection.

<p>Proportion of significant target pathways in the Gene Overexpression Data Collection.</p

Type I error rates: For each method the number (N) and the proportion (%) of rejected hypotheses out of 1000 tested is shown.

<p>Type I error rates: For each method the number (N) and the proportion (%) of rejected hypotheses out of 1000 tested is shown.</p

Overview of the experiments performed to evaluate methods’ performance.

<p>Overview of the experiments performed to evaluate methods’ performance.</p

Overview of the data collections.

<p>Overview of the data collections.</p

Overall assessment of the compared methods.

<p>Overall assessment of the compared methods.</p

Spearman’s correlations coefficients between the gene influence and the number of interactions stratified by interaction type.

<p>Spearman’s correlations coefficients between the gene influence and the number of interactions stratified by interaction type.</p

Effect of topological motifs in SPIA.

<p>Proportions of differentially expressed pathways (DEPs) for individual motifs (columns) at variable induced log2 fold-changes (rows) are displayed as a heatmap. Color bars on the top show influence of the motif, its size and topology (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191154#pone.0191154.s001" target="_blank">S1 Text</a> for details). Note, that colors used for motif topology are unique only among motifs of the same size. The bottom panel shows the influence of the genes in a representation of a topological motif as discovered in Experiment 3.</p