Preparations
Differential expression analysis between compared samples based on tag count data typically starts by preparing two objects: i) a count table matrix where each row indicates a gene, each column a sample, and each cell the number of counts (or reads) mapped to each gene in each sample and ii) a vector that indicates which group each sample belongs to. These data are stored in a TCC class object using the new function. Similar functions of other packages are the DGEList function in the edgeR package, the newCountDataSet function in the DESeq package, the new function in the baySeq package, and so on (see Figure 1a). Consider, for example, a matrix object hypoData consisting of 1,000 rows and six columns and a numeric vector group consisting of six elements, i.e., (1, 1, 1, 2, 2, 2). The first three samples in the matrix are from Group 1 (G1), and the others are from Group 2 (G2). The TCC class object is constructed as follows:
library TCC    data hypoData    group < − c 1 , 1 , 1 , 2 , 2 , 2     tcc  < − new ” TCC ” , hypoData , group