| # attempt at making a minimal conda env for the lesson "Snakemake for Bioinformatics" | |
| # https://carpentries-incubator.github.io/snakemake-novice-bioinformatics | |
| name: snakemake_lesson | |
| channels: | |
| - conda-forge | |
| - bioconda | |
| - defaults | |
| dependencies: | |
| - bioconda::rename | |
| - conda-forge:coreutils |
(Originally posted on twitter, here incorporating responses)
As of version 2.6, there is provisional support for using pandoc using jupyter notebookss (.ipynb files) as input and output format.
Markdown to Jupyter Notebook, and back https://github.com/aaren/notedown
| $ blasr channel_110_read_9_template.fasta AF498417.fasta -m 0 | |
| nMatch: 4151 | |
| nMisMatch: 578 | |
| nIns: 452 | |
| nDel: 898 | |
| %sim: 68.2843 | |
| Score: -10537 | |
| Query: channel_110_read_9_template | |
| Target: gi|20560066|gb|AF498417.1| | |
| Model: a hybrid of global/local non-affine alignment |
| with open(fname) as fh: | |
| for line in fh: | |
| ele = line.strip().split(" ") | |
| if line.startswith('@'): | |
| seq_name = ele[0][1:] | |
| else: | |
| [start, stop, period, copies, | |
| consensus_size, perc_match, perc_indels, | |
| align_score, perc_A, perc_C, perc_G, perc_T, | |
| entropy, cons_seq, repeat_seq, left_flank, right_flank] = ele |