Synnotate

Annotate bacterial and phage genomes — including the genes other tools leave as "hypothetical protein."

Synnotate works out what a gene does from the company it keeps: the genes around it. Because it reads a gene's neighbourhood instead of its sequence, it can put a name to genes that have no known match in any database — the "dark" genes that ordinary annotation leaves blank.

For every gene you get a predicted function and a confidence score. You can also ask Synnotate to show its evidence: whether the same gene neighbourhood turns up in other genomes, and which neighbours led it to the answer.

Install

pip install git+https://github.com/khoa-yelo/Synnotate.git

Then download the data Synnotate needs into a folder of your choice (do this once):

synnotate setup --type prokaryote --dir ./synnotate_db

You point to that folder with --bundle ./synnotate_db whenever you annotate.

Try it

The repository includes a tiny example: a cluster of ribosomal-protein genes with one gene hidden as "hypothetical protein." Synnotate works out what the hidden gene is, from its neighbours alone:

synnotate annotate examples/demo.fna --type prokaryote --bundle ./synnotate_db \
    --gff examples/demo.gff --interpret --out demo

gene_id  annotation  prediction                   confidence  synteny_support  trusted
dcw_03   UNKNOWN     cell division protein FtsL    0.77        0.65             0.95

confidence is a calibrated expected accuracy (a 0.95 means ~95% of such calls are right), and trusted flags the strictest accuracy tier — 0.99, 0.95, or blank — that the call meets from confidence and synteny together.

Annotate your genome

Pick the line that matches what you have:

# You already have an annotated genome (a GFF with product names — e.g. from NCBI, Prokka, or Bakta)
synnotate annotate genome.fna --type prokaryote --bundle ./synnotate_db --gff annotations.gff --interpret --out result

# You have only a genome sequence, not annotated yet
synnotate annotate genome.fna --type prokaryote --bundle ./synnotate_db --backend eggnog --out result

# A phage genome
synnotate annotate phage.fna --type phage --bundle ./synnotate_db --interpret --out result

Add --interpret to include the supporting evidence (synteny and neighbour breakdown). Leave it off for a faster, prediction-only run.

What Synnotate needs from you

Synnotate reads the functions of a gene's neighbours, so those neighbours have to be named first. How that happens depends on your input:

• An already-annotated genome (a GFF with product= names) — Synnotate reads the names directly. Nothing else to install.
• A genome sequence only — Synnotate first names the genes with eggNOG-mapper (install it separately, below).
• A phage — Synnotate uses Pharokka.
• Your own names — give Synnotate a simple gene_id<TAB>function table with --annotations.

To use the sequence-only path, install eggNOG-mapper once:

mamba install -c bioconda eggnog-mapper
download_eggnog_data.py

Your results

Synnotate writes result.synnotate.tsv, one row per gene:

• prediction — the predicted function
• confidence — a calibrated expected accuracy (isotonic regression), so 0.95 means ~95% of such predictions are correct
• confidence_raw — the uncalibrated softmax score, for reference
• top5 — the five most likely functions
• category — a broad functional category

With --interpret, you also get:

• synteny_support — how strongly other genomes back up the call, from 0 to 1
• trusted — the strictest expected-accuracy tier the call clears from calibrated confidence × synteny (0.99, 0.95, or blank); the same trusted-region gate used in the paper
• driving_neighbours — which neighbouring genes led to the prediction

Add --gff-out result.gff to also get an annotated GFF you can load into a genome browser.

Options at a glance

How it works, briefly

Synnotate learns which gene neighbourhoods go with which functions. A gene with no known match still sits in a recognisable neighbourhood, so Synnotate can name it — and every prediction can be traced back to the specific neighbours that supported it.

Citation & license

Paper in preparation. Released under the MIT license — see LICENSE.