Quantile-quantile plot.

<p>Expected p-values assuming a uniform distribution (X-axis; expected −log10(p-value)) were compared to observed p-values (Y-axis; observed −log10(p-value)) in the continuous analysis (A) and dichotomous analysis (B) to evaluate the levels of inflation in test statistics. Expected p-values were calculated based on the uniform distribution assuming each test was independent of others.</p

Significant probes in continuous and dichotomous analysis.

<p>Pearson’s correlation test and Student’s-t test were used for continuous and dichotomous analysis, respectively. (A) From left to right, numbers in Venn diagram indicate the number of probes significant only in continuous analysis, probes significant in both continuous and dichotomous analysis, and probes significant only in dichotomous analysis by p-value cut-off of 0.01. We did not observe differences between shared genes and specific genes in terms of p-values, correlation coefficients, and fold-changes. (B) Probes significant in both analyses (154 probes) were further categorized based on the correlation coefficient and fold-change.</p

Comparison of test statistics.

<p>(A) Pearson’s correlation coefficients in the continuous analysis were compared to fold-changes in the dichotomous analysis to evaluate overall similarity in direction of changes between two analytical methods. The number in each quadrant represents the percentage of probes relative to all probes analyzed. (B) Significance levels in the continuous analysis (−log10(Pearson’s test p-value); X-axis) were compared to those in the dichotomous analysis (−log10(Student’s t-test p-value); Y-axis) in order to evaluate overall similarity in significance between two analytical methods.</p

Overall characteristics of continuous and dichotomous analysis results.

<p>Pearson’s correlation test was performed for continuous analysis. The distribution of correlation coefficient (A) and correlation coefficient vs. significance (i.e., −log10(p-value)) (B) were plotted. For dichotomous analysis, Student’s-t test was used, and the distribution of fold-changes (C) and fold-change vs. significance (−log10(p-value)) (D) were plotted.</p

HD CAGnome.

<p>HD CAGnome is accessible at <a href="http://chgr.partners.org/cgi-bin/cagnome.cgi" target="_blank">http://chgr.partners.org/cgi-bin/cagnome.cgi</a>.</p

Efficiency of dichotomous analysis in capturing significantly correlated genes.

<p>From 107 samples, we randomly selected equal numbers (n = 3 to 41) of HD and controls to perform dichotomous analysis, repeating 1,000 times for each sample size, and compared to continuous CAG length analysis, as described in the text and methods, plotting the resulting percentages in scatter density plots. (A) Variation in the percentage of CAG-length correlated significant differences from continuous analysis that are detected by dichotomous analysis vs. sample size. (B) Variation in the percentage of differences judged significant by dichotomous analysis that are not CAG-length correlated by continuous analysis vs. sample size. Red lines represent linear regression models describing the relationship between sample size and the corresponding performance metric.</p