Investigate a given DGE dataset

This function takes a DGE Data frame and then finds concordant signatures to that. This generates an L1000 signature from the DGE dataset and then uploads that signature to iLINCS to find the relevant concordant (or discordant) signatures

Usage

investigateSignature(
  expr,
  outputLib,
  filterThreshold = NULL,
  filterProp = NULL,
  similarityThreshold = 0.2,
  paired = TRUE,
  outputCellLines = NULL,
  geneColumn = "Symbol",
  logfcColumn = "logFC",
  pvalColumn = "PValue",
  sourceName = "Input",
  sourceCellLine = NA,
  sourceTime = NA,
  sourceConcentration = NA
)

Arguments

expr

A dataframe that has differential gene expression analysis

outputLib

The library to search

filterThreshold

The Filtering threshold.

filterProp

The Filtering proportion.

similarityThreshold

The Similarity Threshold

paired

Logical. Whether to query iLINCS separately for up and down regulated genes

outputCellLines

A character vector of cell lines to restrict the output search to.

geneColumn

The name of the column that has gene symbols

logfcColumn

The name of the column that has log_2 fold-change values

pvalColumn

The name of the column that has p-values

sourceName

(Optional) An annotation column to identify the signature by name

sourceCellLine

(Optional) An annotation column to specify the cell line for the input data

sourceTime

(Optional) An annotation column to specify the time for the input data

sourceConcentration

(Optional) An annotation column to specify the concentration for the input data

Value

A tibble with the the similarity scores and signature metadata

Examples

# Input validation example (no API calls)
mockExpr <- data.frame(
    Symbol = c("TP53", "MYC"),
    logFC = c(2.5, -1.8),
    PValue = c(0.001, 0.01)
)

# Validate library parameter (should produce error)
tryCatch(
    investigateSignature(mockExpr, outputLib = "INVALID"),
    error = function(e) message("Expected error: invalid library")
)
#> Expected error: invalid library

# \donttest{
# This function makes multiple API calls to iLINCS and may take several minutes

# Load differential expression data
inputSignature <- read.table(
    system.file("extdata", "dCovid_diffexp.tsv", package = "drugfindR"),
    header = TRUE
)

# Investigate the signature against chemical perturbagen library
investigatedSignature <- investigateSignature(
    inputSignature,
    outputLib = "CP",
    filterThreshold = 0.5,
    geneColumn = "hgnc_symbol",
    logfcColumn = "logFC",
    pvalColumn = "PValue"
)
head(investigatedSignature)
#> # A tibble: 6 × 14
#>   Source Target    Similarity SourceSignature SourceCellLine SourceConcentration
#>   <chr>  <chr>          <dbl> <chr>           <lgl>          <lgl>              
#> 1 Input  FR-180204     -0.760 InputSig        NA             NA                 
#> 2 Input  Ponatinib      0.751 InputSig        NA             NA                 
#> 3 Input  Suprofen       0.740 InputSig        NA             NA                 
#> 4 Input  SGI-1776       0.739 InputSig        NA             NA                 
#> 5 Input  SCHEMBL6…     -0.733 InputSig        NA             NA                 
#> 6 Input  Lypressin     -0.729 InputSig        NA             NA                 
#> # ℹ 8 more variables: SourceTime <lgl>, TargetSignature <chr>,
#> #   TargetCellLine <chr>, TargetConcentration <chr>, TargetTime <chr>,
#> #   InputSigDirection <chr>, SignatureType <chr>, pValue <dbl>
# }