valearna / ontology_annotations_stats Goto Github PK

This code sets the path to the directory containing the GAF files as a string and gets a list of all GAF files in the directory. It then loops over each GAF file to calculate the overall descriptive statistics for the GAF file, including the total number of annotations, the number of unique genes, the overall number of unique evidences, the number of experimental annotations (based on the evidence codes), and the number of annotations per evidence code. The code then prints the overall descriptive statistics for the GAF file and plots the distribution of the number of annotations per gene and the number of evidences per gene using the hist() function from the matplotlib library. The resulting plots show the frequency of genes with a given number of annotations or evidences. The histograms have a black thin border and blue color. The x-axis and y-axis are both in linear scale for all plots except the complementary cumulative distribution function (CCDF) plot of the number of annotations per gene, which is in log scale on the y-axis.

The code also plots the cumulative distribution function (CDF) of the number of annotations per gene and the complementary cumulative distribution function (CCDF) of the number of annotations per gene using the plot() function from the matplotlib library. The resulting plots show the cumulative frequency and the complementary cumulative frequency of genes with a given number of annotations. The x-axis is in linear scale and the y-axis is in linear scale for the CDF plot and in log scale for the CCDF plot.