recipe bioconductor-sconify

A toolkit for performing KNN-based statistics for flow and mass cytometry data

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/Sconify.html

License:

Artistic-2.0

Recipe:

/bioconductor-sconify/meta.yaml

This package does k-nearest neighbor based statistics and visualizations with flow and mass cytometery data. This gives tSNE maps"fold change" functionality and provides a data quality metric by assessing manifold overlap between fcs files expected to be the same. Other applications using this package include imputation, marker redundancy, and testing the relative information loss of lower dimension embeddings compared to the original manifold.

package bioconductor-sconify

(downloads) docker_bioconductor-sconify

Versions:
1.30.0-01.26.0-01.22.0-01.20.0-01.18.0-01.14.0-01.12.0-01.10.0-11.10.0-0

1.30.0-01.26.0-01.22.0-01.20.0-01.18.0-01.14.0-01.12.0-01.10.0-11.10.0-01.8.0-01.6.0-01.4.0-11.2.0-0

Depends:
  • on bioconductor-flowcore >=2.22.0,<2.23.0

  • on r-base >=4.5,<4.6.0a0

  • on r-dplyr

  • on r-fnn

  • on r-ggplot2

  • on r-magrittr

  • on r-readr

  • on r-rtsne

  • on r-tibble

Additional platforms:

Installation

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-sconify

to add into an existing workspace instead, run:

pixi add bioconductor-sconify

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-sconify

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-sconify

with envname being the name of the desired environment.

Container

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-sconify:<tag>

(see bioconductor-sconify/tags for valid values for <tag>).

Integrated deployment

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

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