Jason Stajich

any assembled transcriptome is an option but I think you still need to give left and right reads for it to select genes with minimal expression level for training step.

I found this worked for me too: ``` $ conda create -p ./fa-test -c bioconda -c conda-forge 'python>=3.8' 'python

you can just download it and refer to the path to it when you run your predict / annotate steps.

But perhaps @nextgenusfs would need to add to this block - it seems like it is archived in an osf.io DOI instead of relying on the busco server https://github.com/nextgenusfs/funannotate/blob/00c207ad4041270a5e0e1f6cff711f697c5d3abc/funannotate/downloads.json#L20

You don't need a valid species name that I know of - anything in the quotes should work - can you try to use single quotes? Name of the file...

yeah if you are doing it through a job script you might have to play with that. This works on our slurm cluster https://github.com/stajichlab/funannotate_template/blob/main/pipeline/03_predict.sh

its a 2GB genome so maybe some memory issues, I also made sure to funannotate: - I downloaded the plant busco from https://busco-data.ezlab.org/v4/data/lineages/viridiplantae_odb10.2020-09-10.tar.gz and Nben genome from ftp://ftp.solgenomics.net/genomes/Nicotiana_benthamiana/assemblies/Niben.genome.v0.4.4.contigs.fasta.gz I'll try...

@nextgenusfs worked on a new step which allows you to process them separately if the names of contigs are know - I think he can answer better than me as...

genemark,eggnog, and signalp need to be installed outside of conda they have separate licenses that do not let them be packaged within conda. https://github.com/biocore/conda-recipes/issues/17 The conda instructions here guide you...

you can set a lower bound for number of training models with `--min_training_models 150` but I think this refers to BUSCO-based training. I think if your training with RNASeq is...