Metadata-Version: 2.4
Name: genotate
Version: 0.17
Summary: A tool to annotate microbial genomes
Home-page: https://github.com/deprekate/genotate
Author: Katelyn McNair
Author-email: deprekate@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: OS Independent
Requires-Python: >3.5.2
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: genbank
Requires-Dist: numpy
Requires-Dist: ruptures
Requires-Dist: tensorflow
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Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
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Introduction
------------

Genotate is a tool to annotate prokaryotic and phage genomes.  It uses scrolling amino-acid
windows in all six frames to distinguish between windows that belong to protein coding gene
regions and those that belong to noncoding regions, in order to determine the coding frame
at every position along the genome.  

* Unlike every other currently available gene caller, Genotate does not rely on *start* and
   *stop* codons in order to predict coding genes<sup>†</sup>


To install `Genotate`,
```sh
 pip install genotate
```

And to run `Genotate` you only need to specify the FASTA formatted genome file
The command to run using the phage models on the provided phiX174 genome is:
```
 genotate.py test/phiX174.fasta -o predictions.gb
```
The command to run using the partially trained bacterial/archaeal models needs the --bacterial flag. Instead of
a FASTA formatted file, you can provide a Genbank formatted file and Genotate will use only the genomic sequence.
```
 genotate.py test/mycoplasma.gbff.gz -o predictions.gb --bacteria
```
**It is recommended to use a GPU to run Genotate since it will take a long time to run prokaryotic 
genomes.**  Genotate will automatically try to run on GPU, if one isn't found it will run on a CPU.

---

† The output of `Genotate` are 'coding region' predictions in GenBank format.  They should match 
with the true coding gene regions, but are not genes per say, since they are not based on *start* and
*stop* codons. Though they have all been trimmed to a *stop* codon after Genotate determines which transation table the genome uses (i.e. whether it performs *stop* codon readthrough).

There are three main phases to the Genotate workflow
1. window classification 
2. change-point detection
3. refinement
   * analyze *stop* codons
   * merge adjacent regions
   * split regions on *stop*
   * adjust ends to a *stop*

Genotate determines the translation table by analyzing the initial coding gene region 
predictions.  There are two outcomes for a *stop* codon that is readthrough: either the *stop* 
codon appears in the middle of a coding gene region or the region is broken into two pieces at 
the *stop* codon. If one of the three known *stop* codons is significantly over represented in the 
middle AND between predicted gene regions, that *stop* codon can be assumed to be read through. 
With the *stop* codon usage now known, adjacent coding regions that are in the same frame are 
merged if there is not a *stop* codon between them. Then the regions are split on any internal 
*stop* codons and the ends adjusted to the nearest *stop* codon.

** The end opposite the *stop* codon is not adjusted to a valid *start* codon since Genotate does not
(yet) have a translation initiation site detection method yet, so the beginning of a gene call may be off by a few codons


Currently the best way to visualize the predictions is in a Genome Viewer application, such
as Artemis by Sanger. The example phiX174.gb GenBank file loaded into Artemis shows the 
gene layout:

![](https://github.com/deprekate/genotate/blob/main/src/genes.png)

The Genotate gene calls in the output predictions.gb file can then be loaded using the 'File>Read An Entry' menu, and the
predictions will be overlaid as grey 'coding regions' in the gene layout window:

![](https://github.com/deprekate/genotate/blob/main/src/predictions.png)


The fact that Genotate calls 9 out of the 10 known coding genes of phiX174, including the fully nested genes *B* and *K*, shows just how
unrivaled Genotate is among currently available gene callers.
