Benchmarking of 4C-seq pipelines based on real and simulated data

With its capacity for high-resolution data output in one region of interest, chromosome conformation capture combined with high-throughput sequencing (4C-seq) is a state-of-the-art next-generation sequencing technique that provides epigenetic insights, and regularly advances current medical research. However, 4C-seq data is complex and prone to biases, and while specialized programs exist, an unbiased, extensive benchmarking is still lacking. Furthermore, neither substantial datasets with fully characterized ground truth, nor simulation programs for realistic 4C-seq data have been published. We conducted a benchmarking study on 54 4C-seq samples from 12 datasets, including original murine BMM, T-cell, and 416B data, and developed a novel 4C-seq simulation software to allow for more detailed comparisons of 4C-seq algorithms on 50 simulated datasets with 10 to 120 samples each. 54 4C-seq samples from 12 datasets, including original murine BMM, T-cell, and 416B data. Re-analyzed samples are from GSE77265, GSE87299, SRP023622, GSE111863, GSE52595, SRA048225, GSE52457, PRJEB5236, GSE62269, GSE101423, and GSE96546. The processed data for these re-analyzed samples are available in a tar archive at the foot of this page.