`grumps`
To update `grumps` via conda: `conda update kabram::grumps`
To update `grumps` via pip: `pip install grumps --upgrade`
`py-grumps`
To update `py-grumps` via conda: `conda update kabram::py-grumps`
`r-grumps`
To update `r-grumps` via conda: `conda update kabram::r-grumps`
To update `r-grumps` via R: `R -e "devtools::install_github('kalebabram/r-grumps')"`
Added
- conda install compatability
- pip install compatability
- R install compatability (via devtools)
- conda-build recipes
- toggle for 'medoid' cleaning step: `-M [yes|no]`
- seperate repository for `r-grumps`: https://www.github.com/kabram/r-grumps.git
- src/ for `grumps`
- Python and R libraries for `grumps`
- `r-grumps` outputs the clustered dendrogram as a .nwk tree file
Changed
- code structure of both `grumps` and `r-grumps`
- GitHub structure of `grumps`
- unified the 'labels' and 'groups' files output by `r-grumps` into one file
- versions of R and Python used in `grumps` and `r-grumps`
- versions of dependencies used in `grumps` and `r-grumps`
Fixed
- issue with `'clique'` mode which could cause `grumps` to produce "species-level"
datasets with multiple species if the dataset had sufficient noise
- Usually only an issue for datasets containing species which have similarity
values barely outside the species boundary (i.e. *Enterococcus faecium* and *Enterococcus
lactis*) or datasets with a high raitio of low-quality genomes relative
to the total number of genomes - i.e. a MAGs dataset
- added 'medoid' cleaning step to `'clique'` mode: `grumps -m clique -M yes distmat.csv`
- defaults to 'yes'
- overall performance of `grumps` by restructering the codebase and loading only the required
portions of `grumps` for the specified workflow (mode, cutoff, etc.)