ERCC

RNA-seq data from biological replicates of 3 cell lines. This dataset
 contains a mixture of spike-in synthetic oligonucleotides that
 are mixed into samples A and B at four mixing ratios: 1/2, 2/3, 1 and 4.

datasets

Given count data from two conditions, it determines which transcripts are differentially expressed across the two conditions using Bayesian inference of the parameters of a bottom-up model for PCR amplification. This model is developed in Ndifon Wilfred, Hilah Gal, Eric Shifrut, Rina Aharoni, Nissan Yissachar, Nir Waysbort, Shlomit Reich Zeliger, Ruth Arnon, and Nir Friedman (2012), <http://www.pnas.org/content/109/39/15865.full>, and results in a distribution for the counts that is a superposition of the binomial and negative binomial distribution.

Gershom Buri

denoiSeq

Differential Expression Analysis Using a Bottom-Up Model

Wilfred Ndifon

ERCC function

A matrix with 92 rows and 10 columns:<dl class="dl-horizontal">
 <dt>Conditions</dt><dd>There are 5 columns for each of the conditions A and B.</dd>
 <dt>Transcripts</dt><dd>There are 92 distinct transcripts distinguishable by
 their names.</dd>
</dl>

Format

ERCC dataset — ERCC

A matrix with 92 rows and 10 columns:<dl class='dl-horizontal'>
 <dt>Conditions</dt><dd>There are 5 columns for each of the conditions A and B.</dd>
 <dt>Transcripts</dt><dd>There are 92 distinct transcripts distinguishable by
 their names.</dd>
</dl>

ERCC: ERCC dataset

Description

Usage

Arguments

Format