Table 2.

Advantages and disadvantages of methods

Methods	Advantages	Disadvantages
DeconRNASeq	∙ Outputs are cell fractions ∙ Open-source implementations available in Python and R ∙ Quick run time	∙ Requires a signature matrix as an input ∙ Performance is highly dependent on the compatibility between signature matrix and mixture data
CIBERSORT	∙ Outputs are cell fractions ∙ Open-source implementations available in Python and R ∙ Web portal available for running method ∙ Good performance on digital cytometry task	∙ Requires a signature matrix as an input ∙ Slow run time
CIBERSORTx B-mode	∙ Outputs are cell fractions ∙ Web portal available for running method ∙ Good performance on digital cytometry task ∙ Eliminates the batch effect between signature matrix and mixture data by adjusting mixture data	∙ Requires a signature matrix as an input
CIBERSORTx S-mode	∙ Outputs are cell fractions ∙ Web portal available for running method ∙ Eliminates the batch effect between signature matrix and mixture data by adjusting signature matrix	∙ Requires a signature matrix as an input ∙ Does not perform as well as CIBERSORTx B-mode
ssGSEA DM	∙ Does not require a signature matrix; it only uses the upregulated gene sets of each cell type ∙ Open-source implementations available in Python and R	∙ Outputs are scores for each cell type rather than cell fractions ∙ Produces similar scores for samples with varying distributions of cell types ∙ Slow run time
SingScore DM	∙ Does not require a signature matrix; it can use both upregulated and downregulated gene sets of each cell type ∙ Open-source implementations available in Python and R ∙ Quick run time	∙ Outputs are scores for each cell type rather than cell fractions ∙ Produces similar scores for samples with varying distributions of cell types