Revisiting the Use of Structural Similarity Index in Hi-C

Abstract

AbstractIdentification of dynamic changes in chromatin conformation is a fundamental task in genetics. In 2020, Galan et al.1 presented CHESS (Comparison of Hi-C Experiments using Structural Similarity), a novel computational algorithm designed for systematic identification of structural differences in chromatin-contact maps. Using CHESS, the same group recently reported that chromatin organization is largely maintained across tissues during dorsoventral patterning of fruit fly embryos despite tissue-specific chromatin states and gene expression2. However, here we show that the primary outputs of CHESS–namely, the structural similarity index (SSIM) profiles–are nearly identical regardless of the input matrices, even when query and reference reads were shuffled to destroy any significant differences. This issue stems from the dominance of the regional counting noise arising from stochastic sampling in chromatin-contact maps, reflecting a fundamentally incorrect assumption of the CHESS algorithm. Therefore, biological interpretation of SSIM profiles generated by CHESS requires considerable caution.