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MSA(Multiple Sequence Alignment) visualization python package for sequence analysis
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moshi4/pyMSAviz
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pyMSAviz is a MSA(Multiple Sequence Alignment) visualization python package for sequence analysis implemented based on matplotlib.This package is developed for the purpose of easily and beautifully plotting MSA in Python.It also implements the functionality to add markers, text annotations, highlights to specific positions and ranges in MSA.pyMSAviz was developed inspired byJalview andggmsa.More detailed documentation is availablehere.
Fig.1 Simple visualization result
Fig.2 Customized visualization result
Python 3.9 or later is required for installation.
Install PyPI package:
pip install pymsavizInstall bioconda package:
conda install -c conda-forge -c bioconda pymsavizOnly simple example usage is described in this section.For more details, please seeGetting Started andAPI Docs.
frompymsavizimportMsaViz,get_msa_testdatamsa_file=get_msa_testdata("HIGD2A.fa")mv=MsaViz(msa_file,wrap_length=60,show_count=True)mv.savefig("api_example01.png")
frompymsavizimportMsaViz,get_msa_testdatamsa_file=get_msa_testdata("MRGPRG.fa")mv=MsaViz(msa_file,color_scheme="Taylor",wrap_length=80,show_grid=True,show_consensus=True)mv.savefig("api_example02.png")
frompymsavizimportMsaViz,get_msa_testdatamsa_file=get_msa_testdata("MRGPRG.fa")mv=MsaViz(msa_file,end=180,wrap_length=60,show_consensus=True)# Extract MSA positions less than 50% consensus identitypos_ident_less_than_50= []ident_list=mv._get_consensus_identity_list()forpos,identinenumerate(ident_list,1):ifident<=50:pos_ident_less_than_50.append(pos)# Add markersmv.add_markers([1])mv.add_markers([10,20],color="orange",marker="o")mv.add_markers([30, (40,50),55],color="green",marker="+")mv.add_markers(pos_ident_less_than_50,marker="x",color="blue")# Add text annotationsmv.add_text_annotation((76,102),"Gap Region",text_color="red",range_color="red")mv.add_text_annotation((112,123),"Gap Region",text_color="green",range_color="green")mv.savefig("api_example03.png")
pyMSAviz provides simple MSA visualization CLI.
pymsaviz -i [MSA file] -o [MSA visualization file]$ pymsaviz --helpusage: pymsaviz [options] -i msa.fa -o msa_viz.pngMSA(Multiple Sequence Alignment) visualization CLI tooloptional arguments: -i I, --infile I Input MSA file -o O, --outfile O Output MSA visualization file (*.png|*.jpg|*.svg|*.pdf) --format MSA file format (Default: 'fasta') --color_scheme Color scheme (Default: 'Zappo') --start Start position of MSA visualization (Default: 1) --end End position of MSA visualization (Default: 'MSA Length') --wrap_length Wrap length (Default: None) --wrap_space_size Space size between wrap MSA plot area (Default: 3.0) --label_type Label type ('id'[default]|'description') --show_grid Show grid (Default: OFF) --show_count Show seq char count without gap on right side (Default: OFF) --show_consensus Show consensus sequence (Default: OFF) --consensus_color Consensus identity bar color (Default: '#1f77b4') --consensus_size Consensus identity bar height size (Default: 2.0) --sort Sort MSA order by NJ tree constructed from MSA distance matrix (Default: OFF) --dpi Figure DPI (Default: 300) -v, --version Print version information -h, --help Show this help message and exitAvailable Color Schemes:['Clustal', 'Zappo', 'Taylor', 'Flower', 'Blossom', 'Sunset', 'Ocean', 'Hydrophobicity', 'HelixPropensity', 'StrandPropensity', 'TurnPropensity', 'BuriedIndex', 'Nucleotide', 'Purine/Pyrimidine', 'Identity', 'None']Clickhere to download example MSA files.
pymsaviz -i ./example/HIGD2A.fa -o cli_example01.png --color_scheme Identity
pymsaviz -i ./example/MRGPRG.fa -o cli_example02.png --wrap_length 80 \ --color_scheme Taylor --show_consensus --show_count
pymsaviz -i ./example/MRGPRG.fa -o cli_example03.png --start 100 --end 160 \ --color_scheme Flower --show_grid --show_consensus --consensus_color tomato
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MSA(Multiple Sequence Alignment) visualization python package for sequence analysis