AFAIK Dfam and Repbase are currently the two best sources of (a variety of) TE sequences.

In my genome annotations I have used RepeatModeler+RepeatMasker and then later used Repbase+tblastx and Dfam+nhmmer to classify them.

The classification process in my pipeline PhyLTR (https://github.com/mcsimenc/PhyLTR) is based on Dfam and Repbase. The process I used for LTR identification is

1. Putative ID with LTRHarvest (based on structural sequence characteristics)
2. Classification-by-homology to Repbase and Dfam
3. Removal of elements without homology to sequences in Repbase or Dfam.

This results in a set of LTR-Rs which are full-length and have evidence that they are being true LTR-Rs.

AFAIK Dfam and Repbase are currently the two best sources of (a variety of) TE sequences.

In my genome annotations I have used RepeatModeler+RepeatMasker and then later used Repbase+tblastx and Dfam+nhmmer to classify them.

The classification process in my pipeline PhyLTR (https://github.com/mcsimenc/PhyLTR) is based on Dfam and Repbase. The process I used for LTR identification is

1. Putative ID with LTRHarvest (based on structural sequence characteristics)
2. Classification-by-homology to Repbase and Dfam
3. Removal of elements without homology to sequences in Repbase or Dfam.

This results in a set of LTR-Rs which are full-length and have evidence that they are LTR-Rs.