View source: R/gess_res_summary.R
gess_res_vis | R Documentation |
The function allows to summarize the ranking scores of selected perturbagens for GESS results across cell types along with cell type classifications, such as normal and tumor cells. In the resulting plot the perturbagens are drugs (along x-axis) and the ranking scores are LINCS' NCS values (y-axis). For each drug the NCS values are plotted for each cell type as differently colored dots, while their shape indicates the cell type class.
gess_res_vis(gess_tb, drugs, col, cell_group = "all", ...)
gess_tb |
tibble in the 'result' slot of the |
drugs |
character vector of selected drugs |
col |
character(1), name of the score column in 'gess_tb', e.g., "NCS" if the result table is from LINCS method. Can also be set as "rank", this way it will show the ranks of each drug in different cell types. |
cell_group |
character(1), one of "all", "normal", or "tumor". If "all", it will show scores of each drug in both tumor and normal cell types. If "normal" or "tumor", it will only show normal or tumor cell types. |
... |
Other arguments passed on to |
plot visualizing GESS results
Subramanian, A., Narayan, R., Corsello, S. M., Peck, D. D., Natoli, T. E., Lu, X., Golub, T. R. (2017). A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. Cell, 171 (6), 1437-1452.e17. URL: https://doi.org/10.1016/j.cell.2017.10.049
gr <- gessResult(result=dplyr::tibble(pert=c("p1", "p1", "p2", "p3"),
cell=c("MCF7", "SKB", "MCF7", "SKB"),
type=rep("trt_cp", 4),
NCS=c(1.2, 1, 0.9, 0.6)),
query=list(up="a", down="b"),
gess_method="LINCS", refdb="path/to/refdb")
gess_res_vis(result(gr), drugs=c("p1","p2"), col="NCS")
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