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bioRxiv · 10.1101/2020.04.27.060145

HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data

Jain, D.·Chu, C.·Alver, B. H.·Lee, S.·Lee, E. A.·Park, P. J.
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Abstract

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.

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Jain, D., Chu, C., Alver, B. H., Lee, S., Lee, E. A., Park, P. J.. 2020-04-28. HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data. https://doi.org/10.1101/2020.04.27.060145

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