hypoData_mg: A simulation dataset for comparing three-group tag count...

In jqsunac/TCC: TCC: Differential expression analysis for tag count data with robust normalization strategies

Description

A simulation dataset, consisting of 1,000 rows (or genes) and 9 columns (or independent biological samples)

Usage

data(hypoData_mg)

Format

hypoData_mg is a matrix of dimension 1,000 times 9.

Details

The hypoData_mg, a matrix object, is a simulation dataset which consists of 1,000 rows (genes) and 9 columns (samples). Each cell of matrix indicates the number of counts to the gene in the sample. The first three columns are produced from biological replicates of, for example, Group 1, the next three columns are from Group2 and the remaining columns are from Group 3; i.e., G1_rep1, G1_rep2, G1_rep3 vs. G2_rep1, G2_rep2, G2_rep3 vs. G3_rep1, G3_rep2, G3_rep3. This data is generated by the simulateReadCounts function with the following parameters (see Examples). The first 200 genes are differentially expressed among the three groups. Of these, the first 140 genes are expressed at a higher level only in Group 1 (G1), the next 40 genes are expressed at a higher level only in G2 and the last 20 genes are expressed at a higher level only in G3. Accordingly, the 201-1000th genes are not differentially expressed (non-DEGs). The levels of differential expression (DE) are four-fold in each group.

Examples

# The 'hypoData_mg' is generated by following commands.
tcc <- simulateReadCounts(Ngene = 1000, PDEG = 0.2,
                          DEG.assign = c(0.7, 0.2, 0.1),
                          DEG.foldchange = c(4, 4, 4),
                          replicates = c(3, 3, 3))
hypoData_mg <- tcc$count

jqsunac/TCC documentation built on March 20, 2021, 4:23 a.m.