HTRNAi: A data set with 960 rows and 6 samples containing normalized...

In markvdwiel/ShrinkBayes: Bayesian analysis of high-dimensional omics data, either Gaussian or counts

A data set with 960 rows and 6 samples containing normalized High-Throughput RNAi data (Gaussian)

Description

This data set is used in the Van de Wiel et al. paper (see below) for illustrations.

Usage

data(HTRNAi)

Format

The format is: num [1:960, 1:6] 0.54317601 0.19539894 0.38832444 -0.03428689 0.60492070 -0.17908612 - attr(*, "dimnames")=List of 2 ..$ : chr [1:10000] "siRNA1" "siRNA2" "siRNA3" "siRNA4" ... ..$ : chr [1:6] "s1" "s2" "s3" "s4" "s5" "s6"

Details

This data set is used to study sensitization of treatment effect by gene silencing in a cancer cell line using cell viability as read-out. The features represent (pools of) siRNA, where each pool targets the same mRNA. The data is assumed to be Gaussian distributed; hence, the examples below can also be used for typical mRNA/miRNA microarray studies. See the example in ShrinkGauss for the design of this study.

References

Van de Wiel MA, De Menezes RX, Siebring-van Olst E, Van Beusechem VW (2013). Analysis of small-sample clinical genomics studies using multi-parameter shrinkage: application to high-throughput RNA interference screening. BMC Med Genom.

Examples

data(HTRNAi)

markvdwiel/ShrinkBayes documentation built on March 27, 2022, 7:47 p.m.