Dataframe of transcriptomic data (natural scale) containing genes as rows and samples as columns. Note: Gene names should be set as row names and duplicates are not allowed. Missing values are not allowed within the expression matrix. Check example- head(example_data): example_data.

Use a value between 0 and 1. Default is 0.6. This is a user defined correlation cut-off to perform feature selection (feature_select). Feature selection aids to enrich the prediction of relative abundance of immune cells by filtering off poorly correlated ImSig genes. To get an idea of what cut-off to use check the results of (gene_stat) and choose a cut-off that displays high median correlation and maintains a high proportion of genes after feature selection.