Generate a heatmap representation of a feature table

Parameters

table : FeatureTable[Frequency]

The feature table to visualize.

metadata : MetadataColumn[Categorical], optional

Annotate the sample IDs with these metadata values. When metadata is present and `cluster`='feature', samples will be sorted by the metadata values.

normalize : Bool, optional

Normalize the feature table by adding a psuedocount of 1 and then taking the log10 of the table.

title : Str, optional

Optional custom plot title.

metric : Str % Choices('sokalmichener', 'yule', 'russellrao', 'rogerstanimoto', 'minkowski', 'correlation', 'jaccard', 'cosine', 'chebyshev', 'euclidean', 'sqeuclidean', 'cityblock', 'matching', 'dice', 'mahalanobis', 'kulsinski', 'seuclidean', 'sokalsneath', 'canberra', 'hamming', 'braycurtis'), optional

Metrics exposed by seaborn (see http://seaborn.pydata.org/generated/sea born.clustermap.html#seaborn.clustermap for more detail).

method : Str % Choices('average', 'complete', 'median', 'centroid', 'single', 'ward', 'weighted'), optional

Clustering methods exposed by seaborn (see http://seaborn.pydata.org/ge nerated/seaborn.clustermap.html#seaborn.clustermap for more detail).

cluster : Str % Choices('features', 'samples', 'none', 'both'), optional

Specify which axes to cluster.

color_scheme : Str % Choices('rocket', 'RdYlBu_r', 'winter', 'viridis', 'BrBG', 'magma_r', 'YlOrBr', 'seismic', 'Set1', 'gist_yarg_r', 'gist_rainbow', 'autumn_r', 'Wistia_r', 'cool_r', 'hsv_r', 'flag', 'Vega20b_r', 'mako_r', 'coolwarm', 'Vega20_r', 'jet', 'cubehelix_r', 'bwr_r', 'brg', 'RdPu', 'gist_ncar', 'RdPu_r', 'cool', 'gnuplot_r', 'Set3', 'ocean_r', 'tab20b', 'tab20b_r', 'OrRd_r', 'Spectral_r', 'gray', 'OrRd', 'prism_r', 'Wistia', 'hot', 'icefire', 'plasma', 'Purples_r', 'viridis_r', 'gnuplot2_r', 'CMRmap', 'YlGnBu_r', 'Set3_r', 'PuRd_r', 'Reds_r', 'gray_r', 'Dark2', 'Vega20b', 'Paired', 'gist_yarg', 'RdYlGn_r', 'Greens', 'YlGnBu', 'tab20', 'gnuplot', 'PuBuGn_r', 'spectral_r', 'tab20c_r', 'gist_rainbow_r', 'hot_r', 'spring_r', 'gist_gray', 'Blues_r', 'Spectral', 'magma', 'GnBu_r', 'inferno_r', 'tab10', 'gist_gray_r', 'seismic_r', 'spring', 'BuPu_r', 'spectral', 'BrBG_r', 'PiYG', 'inferno', 'YlOrBr_r', 'Set1_r', 'YlOrRd_r', 'summer', 'vlag', 'Oranges_r', 'Dark2_r', 'binary_r', 'icefire_r', 'RdYlGn', 'hsv', 'gist_heat', 'PRGn_r', 'pink_r', 'Pastel2_r', 'copper_r', 'BuGn', 'gist_stern_r', 'PuRd', 'gist_earth_r', 'YlOrRd', 'Reds', 'gist_earth', 'Greens_r', 'Vega10', 'ocean', 'brg_r', 'rainbow_r', 'tab20_r', 'Purples', 'Blues', 'Accent', 'afmhot_r', 'Set2_r', 'RdBu', 'Vega20c', 'Pastel1', 'RdGy_r', 'PuBuGn', 'copper', 'PuOr', 'jet_r', 'YlGn_r', 'gist_heat_r', 'PuOr_r', 'bone', 'BuGn_r', 'terrain_r', 'mako', 'Vega20c_r', 'Paired_r', 'PuBu_r', 'tab20c', 'Pastel1_r', 'flag_r', 'plasma_r', 'Oranges', 'autumn', 'bone_r', 'GnBu', 'bwr', 'Greys', 'RdBu_r', 'RdGy', 'winter_r', 'gnuplot2', 'coolwarm_r', 'pink', 'nipy_spectral', 'Greys_r', 'summer_r', 'Vega20', 'BuPu', 'afmhot', 'gist_stern', 'binary', 'PiYG_r', 'YlGn', 'rocket_r', 'cubehelix', 'rainbow', 'Accent_r', 'CMRmap_r', 'PRGn', 'PuBu', 'tab10_r', 'prism', 'vlag_r', 'Set2', 'gist_ncar_r', 'nipy_spectral_r', 'Pastel2', 'terrain', 'RdYlBu', 'Vega10_r'), optional

The matplotlib colorscheme to generate the heatmap with.

Returns

visualization : Visualization