pharm_gen.md

CANDLEfun for pharmacogenomics

US
r doc_date()

Resources

Pharmacodb

library(dplyr)
pdb = src_mysql("pharmacodb", host = "solexadb.cpmth1vkdqqx.us-east-1.rds.amazonaws.com", 
    user = "deeplearn", password = "deeplearn")

Tables available include:

pdb_t = sapply(db_list_tables(pdb$con), function(tblname) tbl(pdb, tblname), 
    USE.NAMES = TRUE, simplify = FALSE)
names(pdb_t)

##  [1] "ar_internal_metadata" "cell_tissues"         "cellosaurus"         
##  [4] "cells"                "datasets"             "dose_responses"      
##  [7] "drug_annots"          "drug_targets"         "drugs"               
## [10] "experiments"          "mol_cells"            "profiles"            
## [13] "schema_migrations"    "source_cell_names"    "source_drug_names"   
## [16] "source_statistics"    "source_tissue_names"  "sources"             
## [19] "targets"              "tissues"

Datasets include:

pdb_t$datasets %>% left_join(pdb_t$source_statistics, c(dataset_id = "id")) %>% 
    knitr::kable()

dataset_id.x dataset_name dataset_id.y cell_lines tissues drugs experiments

---

        1  CCLE                       1          504        23      24         11670
        2  CTRPv2                     2          707        29     139         79903
        3  FIMM                       3          887        25     545        395263
        4  gCSI                       4          410        24      16          6560
        5  GDSC1000                   5           71         1      90          9413
        6  GRAY                       6            0         0       0             0
        7  UHNBreast                  7           15         1       4            52

References