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title: "Open Cancer TherApeutic Discovery (OCTAD) database"
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### Evgenii Chekalin, Billy Zeng, Patrick Newbury, Benjamin Glicksberg, Jing Xing, Ke Liu, Dimitri Joseph, Bin Chen
Edited on October 25, 2021; Compiled on October 25, 2021

# Package overview
As the field of precision medicine progresses, we start to tailor treatments for cancer patients classified not only by their clinical, but also by their molecular features. The emerging cancer subtypes defined by these features require dedicated resources to assist the discovery of drug candidates for preclinical evaluation. Voluminous cancer patient gene expression profiles have been accumulated in public databases, enabling the creation of a cancer-specific expression signature. Meanwhile, large-scale gene expression profiles of chemical compounds became available in recent years. By matching the cancer-specific expression signature to compound-induced gene expression profiles from large drug libraries, researchers can prioritize small molecules that present high potency to reverse expression of signature genes for further experimental testing of their efficacy. This approach has proven to be an efficient and cost-effective way to identify efficacious drug candidates. However, the success of this approach requires multiscale procedures, imposing significant challenges to many labs. Therefore, we present OCTAD (http://octad.org): an open workspace for virtually screening compounds targeting precise cancer patient groups using gene expression features. We have included 19,127 patient tissue samples covering 50 cancer types, and expression profiles for 12,442 distinct compounds.  We will continue to include more tissue samples. We streamline all the procedures including deep-learning based reference tissue selection, disease gene expression signature creation, drug reversal potency scoring, and in silico validation. We release OCTAD as a web portal and a standalone R package to allow experimental and computational scientists to easily navigate the tool. The code and data can also be employed to answer various biological questions.

#Data included within the package.

Package includes all required data for drug repurposing OCTAD pipeline. 
Initialization of the pipeline starts with listing all available samples:
```{r eval=TRUE}
library(octad.db)
#select data
suppressMessages(library(octad.db))
phenoDF=get_ExperimentHub_data("EH7274") #load data.frame with samples included in the OCTAD database. 
head(phenoDF) #list all data included within the package
```

Besides, the package includes examples of the output from diffExp and runsRGES functions from the octad package along with desctiption of the data:
```{r eval=TRUE} 
data("res_example",package='octad.db') #load example res from octad.db
data("sRGES_example",package='octad.db') #load example sRGES from octad.db
```

Please note, this is a database-like package for the main package octad which can be obtained [here](https://bioconductor.org/packages/octad)
After the package will be accepted to the bioconductor, it will be available on the [bioconductor website](https://bioconductor.org/octad)

# Session information 
Here is the output of sessionInfo on the system where this document was compiled:
```{r eval=TRUE} 
sessionInfo()
```
