fishScaleAndMap | R Documentation |
This function is a wrapper for several other functions which aim to scale mFISH data to more closely match RNA-seq data and then map the mFISH data to the closest reference classes. There are several parameters allowing flexability in filtering and analysis.
fishScaleAndMap(
mapDat,
refSummaryDat,
genesToMap = NULL,
mappingFunction = cellToClusterMapping_byCor,
transform = function(x) x,
noiselevel = 0,
scaleFunction = quantileTruncate,
omitGenes = NULL,
metadata = data.frame(experiment = rep("all", dim(mapDat)[2])),
integerWeights = NULL,
binarize = FALSE,
binMin = 0.5,
...
)
mapDat |
normalized data of the MAPPING data set. Default is to map the data onto itself. |
refSummaryDat |
normalized summary data of the REFERENCE data set (e.g., what to map against) |
genesToMap |
which genes to include in the mapping (calculated in not entered) |
mappingFunction |
which function to use for mapping (default is cellToClusterMapping_byCor) The function must include at least two parameters with the first one being mapped data and the second data the reference. Additional parameters are okay. Output must be a data frame where the first value is a mapped class. Additional columns are okay and will be returned) |
transform |
function for transformation of the data (default in none) |
noiselevel |
scalar value at or below which all values are set to 0 (default is 0) |
scaleFunction |
which function to use for scaling mapDat to refSummaryDat (default is setting 90th quantile of mapDat to max of refSummaryDat and truncating higher mapDat values) |
omitGenes |
genes to be included in the data frames but excluded from the mapping |
metadata |
a data frame of possible metadata (additional columns are okay and ignored):
|
integerWeights |
if not NULL (default) a vector of integers corresponding to how many times each gene should be counted as part of the correlation. This is equivalent to calculating a weighted correlation, but only allows for integer weight values (for use with cor). |
binarize |
should the data be binarized? (default=FALSE) |
binMin |
minimum ON value for the binarized matrix (ignored if binarize=FALSE) |
... |
additional parameters for passthrough into other functions |
a list with the following entrees:
mapDat data matrix is passed through
scaled mapDat data matrix
Results of the mapping and associated confidence values (if any)
metadata is passed through unchanged
scaled x and y coordinates (or unscaled if scaling was not performed)
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