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Yes, there are. There are some suggestions in the comments (VG, WhatsHap, GraphAligner, Minigraph). However, to be clear, the current default variant calling algorithm used in the GATK (the haplotype caller) is a graph-based algorithm. It constructs a De Bruijn graph from mapped reads for local assembly around variants. Other tools that also follow this ...

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This might help you for edge in G_nx.edges(data=True): color = "black" weight = edge[2]["weight"] if weight > 0: color = "red" elif weight < 0: color = "blue" edge[2]["color"] = color edge[2]["penwidth"] = abs(weight) This gives you the following graph: ...

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ggplot2 uses factors on the underlying data frame. To have the data plotted in a custom order, apply a custom ordered factor on the underlying dataset. For example, if clusters_per_sample$sample is your custom-ordered vector, do this: clusters_per_sample$sample <- factor(clusters_per_sample$sample, levels = unique(clusters_per_sample$sample), ordered = ...

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You can use as.data.frame() or as_tibble() to convert/coerce your matrix to a data frame or a tibble respectively (Technically a tibble is also a data frame). From there you should be fine with ggplot(). I would not use a "dynamite plot" (this is a box plot with error bars like the one in your question), that type of plots conceal the data! This ...

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You will want to create a self loop for a $k$-mer $s$ whenever $s_1,...,s_{k-1} = s_2,...,s_k$. This will only happen when all of the characters of the $k$-mer are identical, as $s_1=s_2, s_2=s_3,...,s_{k-1}=s_k$.

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