View source: R/consensusConcordants.R
consensusConcordants | R Documentation |
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
consensusConcordants(..., paired = FALSE, cutoff = 0.321, cellLine = NULL)
... |
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. |
A tibble with the filtered and deduplicated results
# 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
)
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