Tutorial

This tutorial walks you through preparing your input data and interpreting the gene prediction output produced by Tiberius.

1. Prepare your genome

Tiberius works with any eukaryotic genomic FASTA file. For best results, follow these guidelines:

File size limit. Files up to 500 MB are accepted. Compressing with gzip (genome.fasta.gz) reduces upload time for large genomes.
Sequence IDs must be unique within the file. Avoid spaces or special characters in FASTA headers; unique sequence IDs up to the first whitespace are required for correct matching with GTF and GFF3 output.

2. Choose a clade model

Select the clade that most closely matches your organism:

Dropdown label	Recommended for
Mammalia	Mammals (human, mouse, bat, …)
Vertebrates	Fish, reptiles, birds, amphibians
Insecta	Insects (Drosophila, Apis, …)
Angiosperms (flowering plants)	Flowering plants (Arabidopsis, rice, …)
Fungi	Fungi (Saccharomyces, Aspergillus, …)
Diatoms	Diatoms (Phaeodactylum, Thalassiosira, …)
Chlorophyta (green algae)	Green algae (Chlamydomonas, …)

If your organism is not covered by any clade, choose the phylogenetically closest one. Tiberius is robust to moderate phylogenetic distance within a kingdom.

3. Submit the job

Go to Submit Job.
Upload your genome file (or use the browse button to locate it).
Select the clade model.
Optionally enter your email address to receive a notification when the job finishes, and tick the consent checkbox.
Click Submit Job.

You will be redirected to a status page. Bookmark it; it updates automatically every 60 seconds. You will also receive an email when the job finishes or fails.

The status page also displays the MD5 checksum of your uploaded genome file (computed from the raw compressed bytes). Compare it with the output of md5sum your_genome.fa.gz to confirm that the file was uploaded intact.

4. Runtime expectations

After submission, your job enters a wait queue before execution begins. Wait time depends on current server load and can range from a few minutes to several hours. The status page shows whether your job is queued or running. Depending on resource availability, jobs may run on CPU or GPU hardware; GPU execution is substantially faster, so actual runtimes can vary significantly from the estimates below.

Organism type	Genome size	Typical runtime
Fungi	10–50 Mb	5–20 min
Insects	100–500 Mb	1–4 h
Plants	120 Mb–2 Gb	1–12 h
Vertebrates	500 Mb–3 Gb	4–24 h
Mammalia	2–4 Gb	12–24 h

Jobs time out after 72 hours. If your job times out, try submitting a subset of chromosomes.

5. Interpret the output

Tiberius produces gene annotation files in both GTF and GFF3 format. Each predicted gene contains one or more transcript models with annotated exons, CDS intervals, start codons, and stop codons. Coding-sequence and protein-sequence FASTA files are also included.

Decompress the result files

All result files are gzip-compressed (.gz). Decompress them with gunzip before passing them to tools that do not accept compressed input:

gunzip tiberius.gtf.gz gunzip tiberius.gff3.gz gunzip coding.fasta.gz gunzip proteins.fasta.gz

Many tools (genome browsers, BLAST, BUSCO, etc.) can read .gz files directly without decompression — check your tool's documentation first.

Example GTF output (first few lines):

Chr1 Tiberius gene 1000 5000 . + . gene_id "g1"; Chr1 Tiberius transcript 1000 5000 . + . gene_id "g1"; transcript_id "g1.t1"; Chr1 Tiberius exon 1000 1200 . + . gene_id "g1"; transcript_id "g1.t1"; Chr1 Tiberius CDS 1050 1200 . + 0 gene_id "g1"; transcript_id "g1.t1"; Chr1 Tiberius exon 2000 2500 . + . gene_id "g1"; transcript_id "g1.t1"; Chr1 Tiberius CDS 2000 2500 . + 2 gene_id "g1"; transcript_id "g1.t1";

You can load this file directly into genome browsers such as JBrowse, IGV, or Ensembl VEP.

6. Local installation

For large genomes, repeated runs, or private data, install Tiberius locally:

git clone https://github.com/Gaius-Augustus/Tiberius.git cd Tiberius python tiberius.py --genome genome.fasta --model_cfg fungi --out tiberius.gtf

See the Tiberius GitHub repository for full installation and usage documentation.