We employed machine learning techniques, including support vector machines, to assess whether the pattern of right-hemispheric resting-state functional connectivity could distinguish left-hemisphere glioma patients from controls, and predict glioma characteristics, including isocitrate dehydrogenase mutation, World Health Organization grade, and relative size. Here, IDH3A is linked to glioma.