Finally, there is so much gratitude for support from
@NIMHgov, @NIH_NINDS, @cziscience, @4DNucleome, and our community in the 4DN that empowered me to do this work.(8/8)

This has been a team effort across the Cremins lab! Special shoutout to Kenneth Pham for helping in crafting and iterating FISHnet, and Harshini Chandrashekar for helping with genomic analyses. (7/8)

Raw pairwise distances from sequential Oligopaints DNA FISH data have limited ability to separate chromatin traces from different cell types. Using FISHnet boundary calls, we can segregate chromatin traces based on cell type. (6/8)

We ensemble sequential Oligopaints DNA FISH data where we mask individual allele data based on FISHnet domain calls and aggregate the masks. We envision that FISHnet will empower studies into how single-allele chromatin conformations results in ensemble features. (5/8)

FISHnet found chromatin domains on published data in human cells (Bintu, Mateo … Boettiger, Zhuang, 2018). When we line up the frequency of single-allele boundary calls we find they line up with bulk Hi-C TADs/subTADs and CTCF/Cohesin peaks. (4/8)

With simulated data, we showed that FISHnet is robust in calling domains in sequential Oligopaints DNA FISH data including when we create datasets with missing signal like real-world data. We also show linear interpolation as an effective tool to deal with missing signal. (3/8)

FISHnet is a graph theory method that capture hierarchical chromatin domains using 4 key steps. (2/8)