Data Analysis in Rare Disease Diagnostics

Abstract

There are more than 8000 documented rare diseases in the
world. While each disease is rare in itself, it is estimated that 1 in every
15 or 20 persons is affected by some rare disease. Most rare diseases
are caused by just one or two small changes in the genome. Identifying
the causative variant from the millions of variants that differentiate one
person’s genome from another is a challenging task. In this article, we
provide an overview of the data processing that takes place during the
multi-stage rare disease diagnosis process. At each stage, we describe
algorithms and methods that are in use in diagnostic laboratories and
also describe how machine learning in general and deep learning in particular
are improving the process.