FemeniasM
commented
1 year ago Dear Yayan, Thank you very much for using this software and for encouraging this feedback. As you note, the best option is always to use the highest quality transcripts, so if we had to choose between two assemblies (one with the genome-guided strategy and one without it) we would choose the genome-guided option. However, usually the tools require a phase of read alignment to the genome. So, if you already have the alignment files, which is the hardest phase of alignment-based TE quantification, you may want to continue using alignment-based software (e.g. TEtranscripts). The idea of using a de novo assembly was an initial step to continue developing the program. When supplied with a de novo transcriptome, the program searches for overlapping transcripts with genes and TEs to use as decoys. I want to go further in the future and identify if these chimeras originate from a TE promoter or a gene promoter, in the first case we should not use it as a decoy. However, if these chimeras originated from a TE promoter represent a significant fraction, it will depend on the study system. I haven't had time to work on this topic for now, but maybe I should integrate an assembler (genome-guided) and abandon the mapping-based strategy to address it. I really hope this comment is useful, best regards martin
Dear Martin,
Thanks for developing this wonderful software for TE expression quantification. I have a question regarding the de novo transcriptome. For non-model organism, we could perform a de novo transcriptome. But for model organisms, like human, should we need to add the reference genome when do de novo transcriptome assembly? Does this have effect on subsequent TE quantification? I think transcriptome assembly with reference genome could improve TE quantification? Right?
Thank you so much in advance Yayan