JSparO (version 1.5.0)

Joint Sparse Optimization via Proximal Gradient Method for Cell Fate Conversion

Description

Implementation of joint sparse optimization (JSparO) to infer the gene regulatory network for cell fate conversion. The proximal gradient method is implemented to solve different low-order regularization models for JSparO.

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Version

Install

install.packages('JSparO')

Monthly Downloads

139

Version

1.5.0

License

GPL (>= 3)

Maintainer

Xinlin Hu

Last Published

August 18th, 2022

Functions in JSparO (1.5.0)

L1normFun

demo_JSparO

demo_JSparO - The demo of JSparO package

L2HalfThr

L2HalfThr - Iterative Half Thresholding Algorithm based on \(l_{2,1/2}\) norm

L2HardThr

L2HardThr - Iterative Hard Thresholding Algorithm based on \(l_{2,0}\) norm

L1twothirdsThr

L1twothirdsThr - Iterative Thresholding Algorithm based on \(l_{1,2/3}\) norm

L1HardThr

L1HardThr - Iterative Hard Thresholding Algorithm based on \(l_{1,0}\) norm

L2SoftThr

L2SoftThr - Iterative Soft Thresholding Algorithm based on \(l_{2,1}\) norm

L1HalfThr

L1HalfThr - Iterative Half Thresholding Algorithm based on \(l_{1,1/2}\) norm

L1SoftThr

L1SoftThr - Iterative Soft Thresholding Algorithm based on \(l_{1,1}\) norm

L2twothirdsThr

L2twothirdsThr - Iterative Thresholding Algorithm based on \(l_{2,2/3}\) norm

L2NewtonThr

L2NewtonThr - Iterative Thresholding Algorithm based on \(l_{2,q}\) norm with Newton method