Title: TCC: tag count comparison package
Author: Koji Kadota, Tomoaki Nishiyama, Kentaro Shimizu
Description: This package provides normalization method of tag count
data by TMM-bayseq-TMM pipeline.  Expected application includes
Depends: R (>= 2.14.0), edgeR (>= 2.4.6), baySeq, NBPSeq

Title: TCC: Differential expression analysis for tag count data with
Author: Sun Jianqiang, Tomoaki Nishiyama, Kentaro Shimizu, and Koji
Description: This package provides functions for performing
differential expression analysis using differentially expressed
gene elimination strategy. A simple unified interface is
provided which encapsulates functions to calculate
normalization factors and estimate differentially expressed
genes defined in edgeR, baySeq, and DESeq packages.  The
appropriate combination provided by TCC allows a more robust
and accurate estimation performed easily than directly using
original packages.  Functions to produce simulation data under
various conditions and to plot the data are also provided.
Depends: R (>= 2.15), edgeR, baySeq, DESeq, ROC, methods

Depends: R (>= 2.15), methods, Biobase(>= 2.13.11), locfit, R (<=

Author: Ying-Wooi Wan, Genevera I. Allen, Matthew L. Anderson, Zhandong Liu
Description: Automatically downloads and processes TCGA genomics and clinical data into a format convenient for statistical analyses in the R environment.

Title: Simple TCGA Data Access for Integrated Statistical Analysis in R

Title: Retrieve Genomic and Clinical Data from TCGA
Description: The Cancer Genome Atlas (TCGA) is a program aimed at improving our understanding of Cancer Biology. Several TCGA Datasets are available online. 'TCGAretriever' helps accessing and downloading TCGA data via the 'cBioPortal' Web Interface (see <http://www.cbioportal.org/web_api.jsp> for more information). Features of 'TCGAretriever' include: 1) it is very simple to use (get all the TCGA data you need with a few lines of code); 2) performance (smooth and reliable data download via 'httr'); 3) it is tailored for downloading large volumes of data.