  Mapper algorithm can be used to build graph-based representations of
high-dimensional data capturing structurally interesting features such as
loops, flares or clusters. The graph can be further annotated with additional
colouring of vertices allowing location of regions of special interest. For
instance, in many applications, such as precision medicine, Mapper graph has
been used to identify unknown compactly localized subareas within the dataset
demonstrating unique or unusual behaviours. This task, performed so far by a
researcher, can be automatized using hotspot analysis. In this work we propose
a new algorithm for detecting hotspots in Mapper graphs. It allows automatizing
of the hotspot detection process. We demonstrate the performance of the
algorithm on a number of artificial and real world datasets. We further
demonstrate how our algorithm can be used for the automatic selection of the
Mapper lens functions.
