Data Processing Parameter Classes

Source: R/normalize.R

Data processing operations in Giotto Suite can be divided into normalization, scaling, and adjustments. These operations can be selected via the factory functions normParam(), scaleParam(), and adjustParam(), respectively.

Requested operations are generated as method-specific param classes that contain all the parameters needed to perform them, editable through $<-.

normParam(method = "default", ...)

scaleParam(method = "default", ...)

adjustParam(method = "limma", ...)

thresholdParam(method = "binarize", ...)

Arguments

method

character. Name of method to use. See details.

...

(optional) Additional named parameters relevant to the param class.

Details

Generated params are S4 objects inheriting from processParam and one of normParam, scaleParam, and adjustParam.

normParam methods

  • "default" - default Giotto normalizations steps (library + log norms)

  • "library" - library normalization

  • "log" - log normalization

  • "osmfish" - osmfish normalization method

  • "pearson" - Lause/Kobak 2020 pearson residuals normalization

  • "quantile" - quantile normalization

  • "tf-idf" - Term Frequency-Inverse Document Frequency

  • "l2" - L2 normalization (also known as Euclidean normalization)

  • "arcsinh" - arcsinh transformation

scaleParam methods

  • "default" - default Giotto scaling steps (scale along features then cells)

  • "zscore" - essentially the same as base::scale(), but with a MARGIN param allowing scaling long either cols or rows

adjustParam methods

thresholdParam methods

  • "binarize" - data binarization (matrices and rasters)

  • "minmax" - value restriction/clamping (matrices and rasters)

See also

processData() for the generic used to apply these params

processExpression() for the way to use this framework with the giotto object