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A p-value-free method for controlling false discovery rates in high-throughput biological data with two conditions

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Clipper

A p-value-free method for controlling false discovery rates in high-throughput biological data with two conditions

Xinzhou Ge, Yiling Chen, Jingyi Jessica Li 2020-09-30

Introduction

Any suggestions on the package are welcome! For suggestions and comments on the method, please contact Xinzhou ([email protected]) or Dr. Jessica Li ([email protected]).

Installation

The package is not on CRAN yet. For installation please use the following codes in R

if(!require(devtools)) install.packages("devtools")
library(devtools)

install_github("JSB-UCLA/Clipper")

A detailed tutorial can be found in our vignette, and on our website: http://shiny2.stat.ucla.edu/Clipper/

Online app website: https://app.superbio.ai/apps/108/

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A p-value-free method for controlling false discovery rates in high-throughput biological data with two conditions

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