Menon, Shreya

AbstractBalanced and apparently balanced chromosome abnormalities (BCAs) have long been known to generate disease through position effects, either by altering local networks of gene regulation or by positioning genes in architecturally different chromosome domains. Despite these observations, identification of genes distally affected by BCAs is often neglected, especially when predicted gene disruptions are found elsewhere in the genome. In this article, we provide detailed instructions on how to run a computational pipeline that identifies relevant candidates for non‐coding BCA position effects. This methodology facilitates quick identification of genes potentially involved in disease by non‐coding BCAs and other types of rearrangements, and expands on the importance of considering the long‐range consequences of genomic lesions. © 2018 by John Wiley & Sons, Inc.