Giter Club home page Giter Club logo

interep's Introduction

interep

Interaction Analysis of Repeated Measure Data

Travis build status CRAN status Codecov test coverage

Extensive penalized variable selection methods have been developed in the past two decades for analyzing high dimensional omics data, such as gene expressions, single nucleotide polymorphisms (SNPs), copy number variations (CNVs) and others. However, lipidomics data have been rarely investigated by using high dimensional variable selection methods. This package incorporates our recently developed penalization procedures to conduct interaction analysis for high dimensional lipidomics data with repeated measurements. The core module of this package is developed in C++. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.

How to install

  • Released versions of interep are available on CRAN (link), and can be installed within R via
install.packages("interep")

Example

library(interep)
data("dat")
## Load the environment factors, lipid factors and the response
e=dat$e
g=dat$z
y=dat$y
## Initial value for the coefficient vector
beta0=dat$coef
## True nonzero coefficients
index=dat$index
b = interep(e, g, y,beta0,corre="e",pmethod="mixed",lam1=dat$lam1, lam2=dat$lam2,maxits=30)
## Cut off the noise
b[abs(b)<0.05]=0
## Compute TP and FP
pos = which(b != 0)
tp = length(intersect(index, pos))
fp = length(pos) - tp
list(tp=tp, fp=fp)

Methods

This package provides implementation for methods proposed in

  • Zhou, F., Ren,J., Li, G., Jiang, Y., Li, X., Wang, W. and Wu, C. (2019). Penalized Variable Selection for Lipid– Environment Interactions in a Longitudinal Lipidomics Study. Genes. 10(12), 1002

interep's People

Contributors

feizhoustat avatar

Stargazers

 avatar  avatar

Forkers

cenwu kunfa yuwen-l

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.