Pairwise ANI (Average Nucleotide Identity) visualization tool
Project description
pairwiseANIviz
Pairwise ANI (Average Nucleotide Identity) visulization tool. This tool is designed to help visualize the results of pairwise comparisons among multiple genomes.
First, Scipy is used to perform hierarchical/agglomerative clustering, followed by generating a clustermap using Seaborn that supports various Matplotlib colormaps.
Main features
- Support various matplotlib colormaps
- Taxonomic classification result can be included to illustrate different taxa
- Specific outrange ANI values can be set (eg. 95% ANI values)
- Multi-format outputs (JPG, PNG, TIFF, SVG, PDF, EPS)
Example
1. Using different matplotlib colormaps
2. With taxonomy indicated by different palettes
3. With ANI values illustrated
4. With outrange ANI values (95%) colored red
Installation
# Dependencies: Matplotlib, Seaborn, Scipy, Pandas
# Install pairwiseANIviz using pip
pip install pairwiseANIviz==1.3
Usage
Options
usage: pairwiseANIviz [options] anifile
positional arguments:
anifile File containing pairwise ANI analysis result.
options:
-h, --help show this help message and exit
-v, --version Show pairwiseANIviz version number and exit.
-o OUTDIR, --outdir OUTDIR
Directory to save the output figures (default 'pairwiseANIviz').
--method {single,complete,average,weighted,centroid,median,ward}
Linkage method to use for calculating clusters (default 'average').
See https://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.hierarchy.linkage.html#scipy.cluster.hierarchy.linkage
--metric {braycurtis,canberra,chebyshev,cityblock,correlation,cosine,dice,euclidean,hamming,jaccard,jensenshannon,kulczynski1,mahalanobis,matching,minkowski,rogerstanimoto,russellrao,seuclidean,sokalmichener,sokalsneath,sqeuclidean,yule}
The distance metric to use (default 'euclidean').
See https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.pdist.html#scipy.spatial.distance.pdist
-cmap COLORMAP, --colormap COLORMAP
Matplotlib colormap used when drawing the heatmap of ANI values (default 'Blues').
See https://matplotlib.org/stable/users/explain/colors/colormaps.html
--figWidth FIGWIDTH Figure width (default '15').
--figHeight FIGHEIGHT
Figure height (default '15').
--linewidth LINEWIDTH
Line width of the main heatmap (default 0.5)
--linecolor LINECOLOR
Line color of the main heatmap (default 'grey').
--rowCluster Draw the row cluster.
--colCluster Draw the column cluster.
--annotation Show ANI values on the plot.
--outrangeValue OUTRANGEVALUE
Cells have ANI values over specific threshold set to red (eg. cells have ANI value >=0.95 set to red) (default 100).
-c CLASSIFICATIONFILE, --classificationFile CLASSIFICATIONFILE
File containing classification result generated by GTDBTk(https://github.com/Ecogenomics/GTDBTk).
-t {domain,phylum,class,order,family,genus,species}, --taxaLevel {domain,phylum,class,order,family,genus,species}
Taxa level illustrated on the plot.
Choose from "domain, phylum, class, order, family, genus, species".
Note that this parameter only works if classification result was input.
--colorPalette COLORPALETTE
Color palette used to return a specified number of evenly spaced hues which are then used to illustrate different taxa (default 'hls').
Note that this parameter only works if classification result was input.
General usage
----------------
1. ANI result visulization **without classification info**:
$ pairwiseANIviz ani_result.txt --rowCluster --colCluster
2. ANI result visulization **with classification info**:
$ pairwiseANIviz ani_result.txt --classificationFile classification_result.tsv --rowCluster --colCluster
Runjia Ji, 2023
Example usage
Suppose you have a txt file (genome_list.txt) contain a list of genomes/MAGs waiting for pairwise comparison, each line is a genome/MAG.
You can choose either fastANI or skani for the pairwise ANI calculation.
Option1. Use fastANI
fastANI --ql genome_list.txt --rl genome_list.txt -t 2 -o ani_result.txt
Option2. Use skani
skani dist --ql genome_list.txt --rl genome_list.txt -t 2 -o ani_result.txt
Then simply run:
pairwiseANIviz ani_result.txt --rowCluster --colCluster
You can adjust the linewidth, colormap, figuresize, wheather to show the x/y labels etc. based on the visualization results. Note that if you don't assign a new output folder, everytime you run it will rewrite the default output.
Citation
If you use pairwiseANIviz in your research, please cite our related paper:
Ji, R., Wan, J., Liu, J. et al. Linking morphology, genome, and metabolic activity of uncultured magnetotactic Nitrospirota at the single-cell level. Microbiome 12, 158 (2024). https://doi.org/10.1186/s40168-024-01837-6
Contact
If you have any questions using pairwiseANIviz, feel free to open an issue or contact me jirunjia@gmail.com.
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