These functions take a gene expression value matrix, a primary covariate vector, an additional known covariates matrix. A two stage analysis is applied to counter the effects of latent variables on the rankings of hypotheses. The estimation and adjustment of latent effects are proposed by Sun, Zhang and Owen (2011). "leapp" is developed in the context of microarray experiments, but may be used as a general tool for high throughput data sets where dependence may be involved.

Install the latest version of this package by entering the following in R:

`install.packages("leapp")`

Author | Yunting Sun <yunting.sun@gmail.com> , Nancy R.Zhang <nzhang@stanford.edu>, Art B.Owen <owen@stanford.edu> |

Date of publication | 2014-07-22 08:52:54 |

Maintainer | Yunting Sun <yunting.sun@gmail.com> |

License | GPL (>= 2) |

Version | 1.2 |

**AlternateSVD:** Alternating singular value decomposition

**FindAUC:** Compute the area under the ROC curve (AUC)

**FindFpr:** Compute the false positive rate at given sizes of retrieved...

**FindPrec:** compute the precision at given sizes of retrieved genes

**FindRec:** compute the recall at given sizes of retrieved genes

**FindTpr:** compute the true positive rate at given sizes of retrieved...

**IPOD:** Iterative penalized outlier detection algorithm

**IPODFUN:** compute the iterative penalized outlier detection given the...

**leapp:** latent effect adjustment after primary projection

**leapp-package:** latent effect adjustment after primary projection

**Pvalue:** Calculate statistics and p-values

**ridge:** Outlier detection with a ridge penalty

**ROCplot:** plot ROC curve

**simdat:** Simulated gene expression data affected by a group variable...

NAMESPACE

data

data/simdat.rda

R

R/leapp.R
MD5

DESCRIPTION

man

man/ROCplot.Rd
man/FindRec.Rd
man/FindPrec.Rd
man/leapp.Rd
man/ridge.Rd
man/IPOD.Rd
man/IPODFUN.Rd
man/FindTpr.Rd
man/Pvalue.Rd
man/leapp-package.Rd
man/simdat.Rd
man/FindFpr.Rd
man/AlternateSVD.Rd
man/FindAUC.Rd
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