weitrix_calibrate_trend: Adjust weights row-wise by fitting a trend to estimated...

In pfh/weitrix: Tools for matrices with precision weights, test and explore weighted or sparse data

Adjust weights row-wise by fitting a trend to estimated dispersions

Description

Dispersions are estimated using weitrix_dispersions. A trend line is then fitted to the dispersions using a gamma GLM with log link function. Weitrix weights are calibrated based on this trend line.

Usage

weitrix_calibrate_trend(weitrix, design = ~1, trend_formula = NULL)

Arguments

weitrix	A weitrix object, or an object that can be converted to a weitrix with as_weitrix.
design	A formula in terms of colData(weitrix or a design matrix, which will be fitted to the weitrix on each row. Can also be a pre-existing Components object, in which case the existing fits (design$row) are used.
trend_formula	A formula specification for predicting log dispersion from columns of rowData(weitrix). If absent, metadata(weitrix)$weitrix$calibrate_trend_formula is used.

Value

A SummarizedExperiment object with metadata fields marking it as a weitrix.

Several columns are added to the rowData:

• deg_free Degrees of freedom for dispersion calculation.

• dispersion_before Dispersion before calibration.

• dispersion_trend Fitted dispersion trend.

• dispersion_after Dispersion for these new weights.

Examples

rowData(simwei)$total_weight <- rowSums(weitrix_weights(simwei))

# To estimate dispersions, use a simple model containing only an intercept
# term. Model log dispersion as a straight line relationship with log total 
# weight and adjust weights to remove any trend. 
cal <- weitrix_calibrate_trend(simwei,~1,trend_formula=~log(total_weight))

# This dataset has few rows, so calibration like this is dubious.
# Predictors in the fitted model are not significant.
summary( metadata(cal)$weitrix$trend_fit )

# Information about the calibration is added to rowData
rowData(cal)


# A Components object may also be used as the design argument.
comp <- weitrix_components(simwei, p=1, verbose=FALSE)
cal2 <- weitrix_calibrate_trend(simwei,comp,trend_formula=~log(total_weight))

rowData(cal2)

pfh/weitrix documentation built on Oct. 13, 2023, 1:01 p.m.