RT Journal Article
SR Electronic
T1 HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.04.27.060145
DO 10.1101/2020.04.27.060145
A1 Dhawal Jain
A1 Chong Chu
A1 Burak Han Alver
A1 Soohyun Lee
A1 Eunjung Alice Lee
A1 Peter J. Park
YR 2020
UL http://biorxiv.org/content/early/2020/04/28/2020.04.27.060145.abstract
AB Hi-C is a common technique for assessing three-dimensional 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 HiTea (Hi-C based Transposable element analyzer) 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. HiTea is available at https://github.com/parklab/HiTea and as a Docker image.Competing Interest StatementThe authors have declared no competing interest.