@article {1574953, title = {HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data}, journal = {Bioinformatics}, volume = {37}, number = {8}, year = {2021}, month = {2021 05 23}, pages = {1045-1051}, abstract = {Hi-C is a common technique for assessing 3D chromatin conformation. Recent studies have shown that long-range interaction information in Hi-C data can be used to generate chromosome-length genome assemblies and identify large-scale structural variations. Here, we demonstrate the use of Hi-C data in detecting mobile transposable element (TE) insertions genome-wide. Our pipeline Hi-C-based TE analyzer (HiTea) capitalizes on clipped Hi-C reads and is aided by a high proportion of discordant read pairs in Hi-C data to detect insertions of three major families of active human TEs. Despite the uneven genome coverage in Hi-C data, HiTea is competitive with the existing callers based on whole-genome sequencing (WGS) data and can supplement the WGS-based characterization of the TE-insertion landscape. We employ the pipeline to identify TE-insertions from human cell-line Hi-C samples. AVAILABILITY AND IMPLEMENTATION: HiTea is available at https://github.com/parklab/HiTea and as a Docker image. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.}, keywords = {Chromatin, Chromosomes, DNA Transposable Elements, Humans, Molecular Conformation, Whole Genome Sequencing}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btaa923}, author = {Jain, Dhawal and Chu, Chong and Alver, Burak Han and Lee, Soohyun and Lee, Eunjung Alice and Park, Peter J*} }