TABLE 2.

Recent tools for the identification of TEs in chromatin structure and chromosome-chromosome interactions.

Tool	Function	Input data	Multimapping handling	References
Crunch	Performs ChIP-seq analysis (mapping, peak calling)	ChIP-seq data and references genome	Multimapping reads are taken into account to avoid a loss of binding peaks in repeated regions; the weight of each of these reads are equally distributed to all mapping locations	Berger et al. (2019)
MapRRcon	Identify proteins binding to TE sequences	ChIP-seq data, references genome and TE consensus sequences	Unique and non-unique aligned reads are extracted and mapped to TE sequences; reads with partial alignment, >3 mismatches and any indels are excluded; Remaining reads are mapped against TE consensus	Sun et al. (2018)
PatChER	Use of chimeric HiC-seq fragments between unique and non-unique reads to identify proteins binding to TE sequences	HiChIP data, HiC-seq data, references genome	Performs random mapping of non-unique reads	Taylor et al. (2021)
HiC-TE	Identification of TEs implicated in 3D conformation	HiC-seq data, references genome	Read mapping performed using Bowtie2	Lexa et al. (2021)
HiTea	Identification of new TE insertions using discarded HiC-seq reads from classical approaches	HiC-seq data, TE consensus, TE annotations in references genome	Identification of close discordant read pairs with one mapping on a unique locus and the other on a TE sequence	Jain et al. (2021)