# Example Data

ClimbTheCliff ships with the in-vitro benchmark dataset from the manuscript: six bulk RNA-seq mixtures (`BULK1`-`BULK6`) pooling four human leukemia cell lines (HL60, K562, SUDHL4, THP1) in known, varying proportions, together with a matching single-cell RNA-seq reference and measured drug sensitivity. All three objects are lazy-loaded with `data()` once the package is attached.

| Object | Description | Manuscript figure |
|---|---|---|
| `sc.es` | scRNA-seq reference, the 4 cell lines profiled individually (2342 cells) | Fig. 2 |
| `bulk.es` | Bulk RNA-seq of the 6 mixtures, with true mixing proportions in `pData(bulk.es)` | Fig. 2 |
| `bulk_auc_data` | Drug sensitivity (AUC) of the 6 mixtures for 7 drugs x 3 timepoints (`sample`, `drug`, `auc` columns, ready for `cliff()`) | Fig. 4A, validated against pure cell-line viability in SFig. 7A |

```r
library(Biobase)
data(sc.es); data(bulk.es); data(bulk_auc_data)

table(sc.es$cellType)               # cells per cell line in the reference
pData(bulk.es)                      # true mixing proportions per bulk sample
unique(bulk_auc_data$drug)          # available drug x timepoint combinations
```

`bulk_auc_data$drug` combines each of the 7 drugs (`5Aza2d`, `Cytarabine`, `Doxorubicin`, `Imatinib`, `Mitomycin`, `Nilotinib`, `Rapamycin`) with each of 3 timepoints (`48h`, `72h`, `96h`), e.g. `"Cytarabine_48h"`. `cliff()` takes one `auc` column at a time, so subset to a single `drug` level before calling it — see the examples in [CLIMB reference](reference/climb.md) and [CLIFF reference](reference/cliff.md).