Package 'drugfindR'

Check if the library is valid

Description

Check if the library is valid

Usage

.validateLibrary(lib)

Arguments

lib	a string of libraries

Value

a boolean

---

Generate a Consensus list of Targets

Description

This function takes a list of (optionally split) concordance dataframes and returns a ranked list of gene or drug targets that have been chose for their maximal similarity to the signature

Usage

consensusConcordants(..., paired = FALSE, cutoff = 0.321, cellLine = NULL)

Arguments

...	One or Two (see paired) Data Frames with the concordants
paired	Logical indicating whether you split the dataframes by up and down regulated in prior analysis
cutoff	A similarity cutoff value. Defaults to 0.321
cellLine	A character vector of Cell Lines you are interested in.

Value

A tibble with the filtered and deduplicated results

Examples

# Get the L1000 signature for LINCSKD_28
kdSignature <- getSignature("LINCSKD_28")

# Get concordant gene knockdown signatures
concordantSignatures <- getConcordants(kdSignature, ilincsLibrary = "KD")

# Get the consensus list of signatures with defaults
consensus <- consensusConcordants(concordantSignatures)

# Get the consensus list of signatures with a different cutoff
consensus <- consensusConcordants(concordantSignatures,
    cutoff = 0.5
)

# Get the consensus list of signatures with a specified cell lines
consensus <- consensusConcordants(concordantSignatures,
    cellLine = c("A549", "MCF7")
)

# Doing a paired analysis
filteredUp <- filterSignature(kdSignature,
    direction = "up", threshold = 0.5
)
filteredDown <- filterSignature(kdSignature,
    direction = "down", threshold = -0.5
)

concordants_up <- getConcordants(filteredUp, ilincsLibrary = "KD")
concordants_down <- getConcordants(filteredDown, ilincsLibrary = "KD")

consensus <- consensusConcordants(concordants_up,
    concordants_down,
    paired = TRUE
)

---

Filter the L1000 Signature

Description

This function filters the L1000 Signature to a given threshold, identifying up-regulated or down-regulated or both up- and down-regulated genes

Usage

filterSignature(signature, direction = "any", threshold = NULL, prop = NULL)

Arguments

signature	A dataframe with the L1000 signature
direction	Direction to filter to. Must be one of "up", "down" or "any". Defaults to "any"
threshold	A Log Fold-Change Threshold to filter at. This can either be a single value or a vector of two values. If a single value is given, then it is assumed to be a symmetric threshold. If two values are given, then the first value is the down-regulated threshold and the second value is the up-regulated threshold. Cannot be specified with prop
prop	A proportion of genes to take from top and bottom. Cannot be specified with threshold

Value

a tibble with the filtered L1000 Signature

Examples

# Get the L1000 signature for LINCSKD_28
kdSignature <- getSignature("LINCSKD_28")

# Filter signature by a specific threshold
filteredSignature <- filterSignature(kdSignature, threshold = 0.5)

# Filter signature by a proportion

filteredSignature <- filterSignature(kdSignature, prop = 0.1)

# Filter Signature to up-regulated genes only by a threshold

filteredSignature <- filterSignature(kdSignature,
    direction = "up", threshold = 0.5
)

# Filter the signature using differing thresholds for up and
# down-regulated genes

filteredSignature <- filterSignature(kdSignature,
    threshold = c(-0.75, 0.5)
)

---

Get Concordant Signatures from iLINCS

Description

This function takes a full or filtered signature and gets concordant signatures from any of the 3 LINCS databases in iLINCS. This can get Overexpression, Knockdown or Chemical Perturbagen signatures.

Usage

getConcordants(signature, ilincsLibrary = "CP")

Arguments

signature	A data frame with the names of genes, their expression value and optionally their p-value
ilincsLibrary	The Library you want to search. Must be one of "OE", "KD" or "CP" for Overexpression, Knockdown or Chemical Perturbagens

Value

A tibble with the list of concordant and discordant signatures

Examples

# Get the L1000 signature for LINCSKD_28
kdSignature <- getSignature("LINCSKD_28")

# Get concordant gene knockdown signatures

concordant_signatures <- getConcordants(kdSignature, ilincsLibrary = "KD")

head(concordant_signatures)

---

Get the L1000 Signature from iLINCS

Description

This function acts as the entrypoint to the iLINCS database. This takes in an ID and returns the signature after making a call to the iLINCS database. The default mode for drugfindR is to use L1000 signatures. However, if you are trying to retrieve a different transcriptomic signature, that is also supported by setting the l1000 parameter to FALSE.

Usage

getSignature(sigId, l1000 = TRUE)

Arguments

sigId	character. The ilincs signature_id
l1000	boolean. If you have a known l1000 signature

Value

a tibble with the L1000 Signature

Examples

# Get the L1000 signature for LINCSKD_28
kdSignature <- getSignature("LINCSKD_28")

---

Investigate a given DGE dataset

Description

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

# Investigate a signature

# Load and prepare the signature
inputSignature <- read.table(system.file("extdata",
    "dCovid_diffexp.tsv",
    package = "drugfindR"
), header = TRUE)


# Investigate the signature

investigatedSignature <- investigateSignature(inputSignature,
    outputLib = "CP",
    filterThreshold = 0.5,
    geneColumn = "hgnc_symbol",
    logfcColumn = "logFC",
    pvalColumn = "PValue"
)

---

Investigate a Given Gene or Drug

Description

This function takes the name of a gene or a drug and a database to use to pull signatures from and then queries iLINCS to get concordant signatures

Usage

investigateTarget(
  target,
  inputLib,
  outputLib,
  filterThreshold = 0.85,
  similarityThreshold = 0.321,
  paired = TRUE,
  inputCellLines = NULL,
  outputCellLines = NULL
)

Arguments

target	The name of the gene or drug
inputLib	One of "OE", "KD" or "CP". Marks the database to use.
outputLib	One of "OE", "KD" or "CP". Marks the database to query.
filterThreshold	The Filtering threshold.
similarityThreshold	The Similarity Threshold
paired	Logical. Whether to query iLINCS separately for up and down regulated genes
inputCellLines	A character vector of cell lines to restrict our search for input signatures to.
outputCellLines	A character vetor of cell lines to restrict the output search to.

Value

A tibble with the the similarity scores and signature metadata

Examples

# Search the whole iLINCS database for top concordant signatures for an
# ABL2 knockdown signature

investigatedSignature <- investigateTarget("ABL2",
    inputLib = "KD",
    outputLib = "CP",
    filterThreshold = 0.5
)

---

Load the correct metadata table

Description

Load the correct metadata table

Usage

loadMetadata(lib)

Arguments

lib	a string. One of "OE", "KD" or "CP"

Value

a tibble

---

Prepare an L1000 Signature froma given differential gene expression output

Description

This function takes a differential gene expression output from any pipeline like edgeR or DeSeq2 or any that give you the gene symbol, log_2 fold-change and p-value and transforms that into an L1000 signature for later processing.

Usage

prepareSignature(
  dge,
  geneColumn = "Symbol",
  logfcColumn = "logFC",
  pvalColumn = "PValue"
)

Arguments

dge	A dataframe-like object that has the differential gene expression information
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

Value

A tibble with the L1000 signature.

Examples

# Prepare an L1000 signature from a differential gene expression output

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

signature <- prepareSignature(inputSignature,
    geneColumn = "hgnc_symbol",
    logfcColumn = "logFC", pvalColumn = "PValue"
)

head(signature)

---

Stop if the libraries are invalid

Description

Stop if the libraries are invalid

Usage

stopIfInvalidLibraries(libs)

Arguments

libs	a character vector of libraries

Value

a stop if the libraries are invalid

---

Rename the Target-Related Columns

Description

Rename the Target-Related Columns

Usage

targetRename(inputNames)

Arguments

inputNames

A character vector of input_names

Value

A character vector of new names

---

Check if the libraries input are valid

Description

Check if the libraries input are valid

Usage

validateLibraries(libs)

Arguments

libs	a character vector of libraries

Value

a boolean

---