README.md

In emodoro/dEMO: Differential Expression and confidencial estimation for FC

dEMO

dEMO is a R package that implements both dEMO test, a new method which allows carrying out a Differential Expression Analysis from RNA-seq data sets, and estimating confidencial intervals for Fold Change.

Functions

Several functions have find developed in dEMO package for ahead three principal points:

1. Building confidence intervals for Fold Change :
   • When data sets store data expression such that each row from expression matrix is independent on the rest, we suggest employ dEMO::dEMOOD1sci function. This situation could pops up when each row from data set cames from a independent study such as data simulation following a negative binomial distribution, each row with a n trials and r succeses.
   • When data sets came from RNA-seq assays, each row i depends on the rest of rows, since each row is a feature (gene) measured from the sample stored into column j. Here, we suggest to use dEMO::dEMOODci function.
2. Differential Expression Analysis : dEMO::dEMObuODlmTest function allows carrying out dEMO test method, which is a hypothesis testing where hull hpothesis correspond to $\log_2{Fold Change}=0$ and alternative hypothesis to $\log_2{Fold Change}\ne0$.
3. Comparing different Differential Expression Analysis Methods. In orther to testing the performance for several Differential Expression Analysis methods, between them, several functions have been developed, which allows:
   • Building ROCs: dEMO::ROCcurve.
   • Getting Area under ROCs: dEMO::ROCAreas, dEMO::ROCAreas005 and dEMO::ROCAreasData.
   • Building FDR curves: dEMO::FDRcurve
   • Testing the capability of controlling Type I error: dEMO::TIerror.

Install dEMO R package.

Since several vignettes have been developed, we suggest download dEMO repository in local computer and then employ devtools::build.

emodoro/dEMO documentation built on May 28, 2019, 12:57 p.m.