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"Coloring by metadata mapping file: Additionally, using the supplied mapping file and a specific category or any combination of the available categories. When using the -b option, the user can specify the coloring for multiple header names, where each header is separated by a comma. The user can also combine mapping headers and color by the combined headers that are created by inserting an '&&' between the input header names. Color by 'Treatment' and by the result of concatenating the 'DOB' category and the 'Treatment' category:\r\n",
"PCoA plot with an explicit axis: Create a PCoA plot with an axis of the plot representing the 'DOB' of the samples. This option is useful when presenting a gradient from your metadata e. g. 'Time' or 'pH':\r\n",
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" make_emperor.py -i unweighted_unifrac_pc.txt -m Fasting_Map.txt -a DOB -o pcoa_dob\r\n",
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"\r\n",
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"PCoA plot with an explicit axis and using --missing_custom_axes_values: Create a PCoA plot with an axis of the plot representing the 'DOB' of the samples and define the position over the gradient of those samples missing a numeric value; in this case we are going to plot the samples in the value 20060000. You can select for each explicit axis which value you want to use for the missing values:\r\n",
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" make_emperor.py -i unweighted_unifrac_pc.txt -m Fasting_Map_modified.txt -a DOB -o pcoa_dob_with_missing_custom_axes_values -x 'DOB:20060000'\r\n",
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"\r\n",
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"PCoA plot with an explicit axis and using --missing_custom_axes_values but setting different values based on another column: Create a PCoA plot with an axis of the plot representing the 'DOB' of the samples and defining the position over the gradient of those samples missing a numeric value but using as reference another column of the mapping file. In this case we are going to plot the samples that are Control on the Treatment column on 20080220 and on 20080240 those that are Fast\r\n",
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" make_emperor.py -i unweighted_unifrac_pc.txt -m Fasting_Map_modified.txt -a DOB -o pcoa_dob_with_missing_custom_axes_with_multiple_values -x 'DOB:Treatment==Control=20080220' -x 'DOB:Treatment==Fast=20080240'\r\n",
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"\r\n",
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"Jackknifed principal coordinates analysis plot: Create a jackknifed PCoA plot (with confidence intervals for each sample) passing as the input a directory of coordinates files (where each file corresponds to a different OTU table) and use the standard deviation method to compute the dimensions of the ellipsoids surrounding each sample:\r\n",
"Jackknifed PCoA plot with a master coordinates file: Passing a master coordinates file (--master_pcoa) will display the ellipsoids centered by the samples in this file:\r\n",
"BiPlots: To see which taxa are the ten more prevalent in the different areas of the PCoA plot, you need to pass a summarized taxa file i. e. the output of summarize_taxa.py. Note that if the the '--taxa_fp' has fewer than 10 taxa, the script will default to use all.\r\n",
"BiPlots with extra options: To see which are the three most prevalent taxa and save the coordinates where these taxa are centered, you can use the -n (number of taxa to keep) and the --biplot_fp (output biplot file path) options.\r\n",
"Drawing connecting lines between samples: To draw lines betwen samples within a category use the '--add_vectors' option. For example to connect the lines by the 'Treatment' category.\r\n",
"Drawing connecting lines between samples with an explicit axis: To draw lines between samples within a category of the mapping file and have them sorted by a category that's explicitly represented in the 3D plot use the '--add_vectors' and the '-a' option.\r\n",
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" make_emperor.py -i unweighted_unifrac_pc.txt -m Fasting_Map.txt --add_vectors Treatment,DOB -a DOB -o sorted_by_DOB\r\n",
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"\r\n",
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"Compare two coordinate files: To draw replicates of the same samples like for a procustes plot.\r\n",
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