recipe bioconductor-celltrails

CellTrails is an unsupervised algorithm for the de novo chronological ordering, visualization and analysis of single-cell expression data. CellTrails makes use of a geometrically motivated concept of lower-dimensional manifold learning, which exhibits a multitude of virtues that counteract intrinsic noise of single cell data caused by drop-outs, technical variance, and redundancy of predictive variables. CellTrails enables the reconstruction of branching trajectories and provides an intuitive graphical representation of expression patterns along all branches simultaneously. It allows the user to define and infer the expression dynamics of individual and multiple pathways towards distinct phenotypes.






package bioconductor-celltrails

(downloads) docker_bioconductor-celltrails



Depends bioconductor-biobase


Depends bioconductor-biocgenerics


Depends bioconductor-singlecellexperiment


Depends bioconductor-summarizedexperiment


Depends r-base


Depends r-cba

Depends r-dendextend

Depends r-dtw

Depends r-envstats

Depends r-ggplot2

Depends r-ggrepel

Depends r-igraph

Depends r-maptree

Depends r-mgcv

Depends r-reshape2

Depends r-rtsne



With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-celltrails

and update with:

conda update bioconductor-celltrails

or use the docker container:

docker pull<tag>

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