clue {slinky} | R Documentation

## clue

### Description

Wrapper for clue.io REST calls

### Usage

    clue(x, endpoint = c("sigs", "cells", "genes", "perts", "plates", "profiles",
      "rep_drugs", "pcls"), fields = "", where_clause = NULL, ids = NULL,
      limit = 0, count = FALSE, unpack_sigs = TRUE, poscon = c("omit",
      "keep"), cl = NULL, verbose = FALSE)

    ## S4 method for signature 'Slinky'
    clue(x, endpoint = c("sigs", "cells", "genes", "perts",
      "plates", "profiles", "rep_drugs", "pcls"), fields = "",
      where_clause = NULL, ids = NULL, limit = 0, count = FALSE,
      unpack_sigs = TRUE, poscon = c("omit", "keep"), cl = NULL,
      verbose = FALSE)

### Arguments

`x` | a Slinky Object
`endpoint` | The endpoint to query. Default is 'sigs'.
`fields` | Optional vector of fields to return.
`where_clause` | Optional where_clause clause. Must be named list (e.g. list(field='value')
`ids` | Optional vector of ids to fetch for sigs or profiles endpoints. Should not be used together with where_clause or count.
`limit` | Optional limit to number of instances (samples to return
`count` | Should we just return the count of intances satisfying the query rather than the data? Default is FALSE.
`unpack_sigs` | The sigs endpoint returns multiple distil_ids per row. Should we unpack these to one per row?
`poscon` | Instances of type `trt_poscon` are recoded as `trt_cp` in clue.io's `sigs` endpoint. This can lead to unexpected results downstream. To keep these instances, specify `poscon='keep'`
`cl` | Optional cluster object to parallelize this operation. If verbose is TRUE, use this pattern in order for progress bar to update: `cl <- parallel::makeCluster(4, outfile=\"\")`
`verbose` | Do you want to know how things are going? Default is false.

### Value

Data returned by Slinky.api as a data.frame

### Examples

    # for build/demo only.  You MUST use your own key when using the slinky
    # package.
    user_key <- httr::content(httr::GET('https://api.clue.io/temp_api_key'),
                              as='parsed')$user_key
    sl <- Slinky(user_key,
                     system.file('extdata', 'demo.gctx',
                          package='slinky'),
                     system.file('extdata', 'demo_inst_info.txt',
                         package = 'slinky'))
    amox <- clue(sl, where_clause = list("pert_iname" = "amoxicillin",
                                        "cell_id" = "MCF7",
                                        "is_gold" = TRUE))

[Package slinky version 1.0.2 Index]