Figure 2

Microarray and RNA-Seq show highly consistent gene expression metrics. A) Pearson correlations of absolute expression levels between 115 replicate sample pairs using both methods. B) Average log2 expression levels between RNA-Seq (TPM) and microarray (intensity) are strongly correlated. A subset of bright probes (red) show particularly increased intensity in microarray. C) Histograms showing distribution of gene expression measures across all samples with microarray (top) and RNA-Seq (bottom). Note the extended leftward tail on the RNA-Seq distribution indicating the lower range sensitivity. D) Number of genes called present in microarray (light grey) and RNA-Seq (dark grey) for at least 5%, 50%, and 95% of samples. Horizontal black bars indicate the percentage of overlapping genes called as present using both methods. E-F) Correlation of differential expression between brains based on microarray intensity (E) and RNA-Seq TPM values (F). Each of 100,000 points shows the log2 fold change of a random gene between two random non-neocortical regions as measured by brain 1 (x-axis) and brain 2 (y-axis). G) Correlation of differential expression between methods in the training set (brain 2). Labeling as in E, except fold changes correspond to RNA-Seq (x-axis) and microarray (y-axis). H) Number of genes differentially expressed between non-neocortical regions based on an ANOVA, for various p-value thresholds. Colors and lines as in (D).