Made genome configurable for GRO-seq, tried to debug rpy2 uncachable
exceptions.

This is to limit clutter from old analyses.

Added function to compute seed disposition from bowtie2 settings.

From the results, it seems that these settings are OK for the smallest
size range, but not for longer reads.

The ValueError was:
`Invalid file path or buffer object type: <class 'snakemake.io.Namedlist'>`

This was due to an extra comma at the end of the return of `source_norm_file`.

Some wildcard did not get properly substituted.

The remapping is done with one mismatch allowed in the seed. It happened
that very little mapped reads had mismatches, although read-through
reads can have some.

Currently goes from demultiplexing to mapping, via trimming and
deduplicating. The mapping is performed on 3 read type:
- adapt_nodedup (the adaptor was found, and the reads were trimmed but
  not deduplicated)
- adapt_deduped (the adaptor was found, and the reads were trimmed and
  deduplicated)
- noadapt_deduped (the adaptor was not found, and the reads were trimmed
  and deduplicated)

The trim_and_dedup script currenly assumes that two low-diversity zones
are present, and ignores them for deduplication:

NNNNNGCACTANNNWWW[YYYY]NNNN
1---5 : 5' UMI
     6--11: barcode (lower diversity)
          12-14: UMI
            15-17: AT(or GC?)-rich (low diversity)
                [fragment]
                       -4 -> -1: 3' UMI

It may be a problem to deduplicate taking into account the end of the
reads, which tends to be of lower quality. The reads with errors will be
over-represented. That is why we decided to also look at the
non-deduplicated reads.