Learning Principal Graphs with DDRTree

Provides an implementation of the framework of reversed graph embedding (RGE) which projects data into a reduced dimensional space while constructs a principal tree which passes through the middle of the data simultaneously. DDRTree shows superiority to alternatives (Wishbone, DPT) for inferring the ordering as well as the intrinsic structure of the single cell genomics data. In general, it could be used to reconstruct the temporal progression as well as bifurcation structure of any datatype.


DDRTree

An R implementation of the DDRTree algorithm for learning principal graphs

Reference manual

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install.packages("DDRTree")

0.1.6 by Brent Ewing, 7 months ago


Browse source code at https://github.com/cran/DDRTree


Authors: Xiaojie Qiu [aut] , Cole Trapnell [aut] , Qi Mao [aut] , Li Wang [aut] , Brent Ewing [cre]


Documentation:   PDF Manual  


Artistic License 2.0 license


Imports Rcpp

Depends on irlba

Linking to Rcpp, RcppEigen, BH


See at CRAN