Supplementary Figure 4: FIT’s performance varies across CSPs but can be predicted based on the input mouse gene expression.
From: Found In Translation: a machine learning model for mouse-to-human inference
(a) Classification of CSPs in each disease into the five performance classes shown in Fig. 2d. FIT-improved disease set (marked in bold) are diseases in which most of the CSPs were improved by FIT (major or minor signal improvement). The diseases are sorted by the number of CSPs that were improved. (b) A distinction between good and poor FIT performance is apparent in the first two principal components based the mouse expression of 4,957 genes. A good FIT performance was defined as true positive ratio > 1.1, meaning that FIT was able to identify at least 10% more human-relevant genes compared to the mouse.
