recipe r-scistreer

Fast maximum-likelihood phylogeny inference from noisy single-cell data using the 'ScisTree' algorithm by Yufeng Wu (2019) <doi:10.1093/bioinformatics/btz676>. 'scistreer' provides an 'R' interface and improves speed via 'Rcpp' and 'RcppParallel', making the method applicable to massive single-cell datasets (>10,000 cells).

Homepage:

https://github.com/kharchenkolab/scistreer, https://kharchenkolab.github.io/scistreer/

License:

GPL3 / GPL-3.0-only

Recipe:

/r-scistreer/meta.yaml

package r-scistreer

versions:

1.2.0-0

depends bioconductor-ggtree:

>=3.14.0,<3.15.0a0

depends libgcc:

>=13

depends libstdcxx:

>=13

depends r-ape:

depends r-base:

>=4.4,<4.5.0a0

depends r-dplyr:

depends r-ggplot2:

depends r-igraph:

depends r-paralleldist:

depends r-patchwork:

depends r-phangorn:

depends r-rcpp:

depends r-rcpparmadillo:

depends r-rcppparallel:

depends r-reshape2:

depends r-rhpcblasctl:

depends r-stringr:

depends r-tidygraph:

requirements:

additional platforms:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install r-scistreer

and update with::

   mamba update r-scistreer

To create a new environment, run:

mamba create --name myenvname r-scistreer

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/r-scistreer:<tag>

(see `r-scistreer/tags`_ for valid values for ``<tag>``)

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