a python package for graphing emapper results
Project description
egger
a python package to plot results from eggnog-mapper
Description
egger
can plot COG functional annotations from eggnog-mapper annotation files.
The repository for eggnog-mapper can be found, here.
It has two modes:
compare
: compares the correlation of COG categories across several genomes.window
: plots sliding window plots of COG category distribution across a genome.
See below for usage examples.
Installation
You can install egger with pip
.
Either use the PyPI installation: pip install egger
.
Or, clone this repository and install manually.
egger
only requires Python dependencies, which should be installed automatically.
Usage and Example Output
As described above, egger
has two modes:
compare
compare output
egger compare
will calculate the correlation of COG category annotations across genomes and build a dendrogram-heatmap.
It will write this as .svg file along with the raw data in .tsv formats. It can perform Spearman's rank (-s
) or Pearson's (-p
) correlation.
It can also produce barcharts (-b
). Use: egger compare -h
for more information.
Here is an example using this repository's example_data/outputs/compare_outputs
as the working directory:
$ egger compare -b barchart -s spearmans -p pearsons ../../inputs/annotations/*
compare output
These heatmaps can help identify relationships between genomes or other sequences.
window
window usage
egger window
will take eggnog-mapper annotations and plot them using a sliding window.
Please note, as eggnog-mapper annotations do not contain location data, the original genome used for the analysis is also required.
You will also need to define outputs with -swo
or -swp
. You can also modify the window and step size using. Use: egger window -h
for more information.
Here is an example using this repository's example_data/outputs/window_outputs
as the working directory:
egger window -a ../../inputs/annotations/Lactococcus_lactis.annotations -g ../../inputs/genomes/Lactococcus_lactis.gb -swo output_ -swp plot_
window output
This will produce two files:
-swo
writes a .tsv file with the raw data used for plotting the sliding window.-swp
writes a .html file for an interactive plot of the sliding window data.
This analysis is particularly useful for finding regions of the genome that are dedicated to a specific function. In the example, Lactococcus lactis has three notable islands for the COG categories J, M and P (among others).
Citation
Coming soon...
Patch Notes
- v1.0.0 - Initial version
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