This is to generate a heatmap to check the result of PAM50 prediction.
plotPAM50(es, PAM50.pred, add_labels = NULL, cluster_rows = F, cluster_cols = F, scale = "row", ...)
es | dataframe, rows are genes columns are samples. Row names has to be EntrezID. |
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PAM50.pred | array of each sample's PAM50 label (you can get the label using PAM50 function) |
add_labels | Additional argument for adding extra labels (dataframe) to show in the heatmap. Labels have to be the same sample order as PAM50.pred |
cluster_rows | bool (defaul = False), indicate whether to reorder the genes. Default uses Parker et al. paper's gene order. |
cluster_cols | bool (defaul = False), indicate whether to reorder the samples. |
scale | string (default = "row"). Options are "none", "row", or "column". This is to rescale data (calculate zscore) based on row, column or no rescaling. |
... | other parameters passed onto pheatmap, for instance, main = "Treatment Arms". |