This is to limit clutter from old analyses.

This is now used for degradation efficiency too.
The general concept is to compute a fold of TPM bewteen library types.
TE is for Ribo / RNA, DE is for Degradome / RNA.

Duplicates were due to `protein_coding_*` biotypes. Those were removed
in join_all_counts.

Also started producing more quantifications (RPK, TPM). TPM still needs
figuring out how to treat duplicate gene IDs when gathering count
results from several biotypes.

Still a lot of work to do.

This will enable more flexibility to specify groups of libraries to be
plotted on one figure. This is currently used by metagene profiles.

Also did a little code cleaning and added a gene list to the small RNA
pipeline.

Rasterizing might make pdfs lighter.

Escaping underscore for tex-compatibility is now idempotent.

Also added a missing tex-compatibility escaping.

Normalization is by non-structural mappers.

Fixing base composition files. Use mappy instead of pyGATB.

Inactivating metaprofile around piRNA target sites due to problems with
bedtools.

Moved cleanup and backup to common library.

Optional automatic directory layout.

Made paired scatterplot plotting function part of libhts as
`plot_paired_scatters`. Modifications in small RNA-seq pipeline not
tested.

Factorized linking to raw data.

It turns out that using `include:` can fail when there are symlinks in
the path to the snakefile.