v0.11.1

Minor Release

• Preliminary hard-RLE model for R9.4.1
• --regions argument can now be a .bed file.
• Detect NaNs during training and halt early.
• Workaround pysam interface changes (for conda package).
• Support soft-RLE network training.

This release includes an experimental consensus mode using run-length encoded alignments. Use of this algorithm can be specified using the new "rle" model:

medaka_consensus -m r941_min_high_g340_rle -i basecalls.fasta -d draft.fa

Please do not attempt to use the "Source code" assets attached below for running medaka, they do not include medaka's model files.