Figure 1
From: TCC: an R package for comparing tag count data with robust normalization strategies
DEGES-based analysis pipelines in TCC. (a) Main functions for obtaining DE results from tag count data in individual packages (edgeR, DESeq, baySeq, and TCC). The analysis pipelines of the packages can be roughly divided into two steps after importing the input data (black squares): (i) calculating normalization factors (blue solid squares) and (ii) estimating degrees of DE for each gene (blue dashed squares). (b) Outline of the DEGES-based normalization methods implemented in TCC. The key concept of DEGES in our calcNormFactors function is to remove data flagged as potential DEGs in step 2 before calculating normalization factors in step 3. Note that steps 2 and 3 in DEGES can be repeatedly performed in order to obtain more robust normalization factors and the function accepts many iterations n (i.e., n = 0 ~ 100).