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Karen (version 1.0)

Kalman Reaction Networks

Description

This is a stochastic framework that combines biochemical reaction networks with extended Kalman filter and Rauch-Tung-Striebel smoothing. This framework allows to investigate the dynamics of cell differentiation from high-dimensional clonal tracking data subject to measurement noise, false negative errors, and systematically unobserved cell types. Our tool can provide statistical support to biologists in gene therapy clonal tracking studies for a deeper understanding of clonal reconstitution dynamics. Further details on the methods can be found in L. Del Core et al., (2022) .

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Version

Install

install.packages('Karen')

Monthly Downloads

165

Version

1.0

License

GPL-3

Maintainer

Luca Del Core

Last Published

September 15th, 2022

Functions in Karen (1.0)

Y_RM

Rhesus Macaque clonal tracking dataset
Y_CT

Clonal tracking data from clinical trials
get.sMoments

Get the first two-order smoothing moments from a fitted Kalman Reaction Network.
get.sMoments.avg

Get the clone-average of the first two-order smoothing moments from a fitted Kalman Reaction Network.
get.cdn

Get the cell differentiation network from a fitted Kalman Reaction Network.
get.fit

Fit the state-space model to a clonal tracking dataset
nearestPD

Nearest Positive Definite Matrix
get.sim.trajectories

Simulate a clonal tracking dataset from a given cell differentiation network.