make.positive.control.plot: Make heatmaps of positive control correlations

In uclahs-cds/public-R-NanoStringNormCNV: Helper Functions to Normalize NanoString CNV Data

Make heatmaps of positive control correlations

Description

Create heatmaps of correlations between target concentrations and actual counts of positive control probes.

Usage

make.positive.control.plot(correlations, covs = NULL, print.x.labels = TRUE)

Arguments

correlations	A data-frame of R squared values by sample ID. See output of positive.control.qc
covs	A data-frame of sample annotation used to create plot covariates. Recommended to use output of load.phenodata. Accepts sample 'Cartridge' and 'Type' information; requires 'SampleID' column to match to sample IDs in 'correlations' variable. Defaults to NULL
print.x.labels	Whether to display the sample IDs on the heatmap's x-axis. Defaults to TRUE

Details

Creates two heatmaps that display the sample R squared values, ascending.

Value

None

Author(s)

Cindy Yao and Emilie Lalonde

Examples

## Not run: 
	#load raw data
	data(NanoString.DNA.raw);
	data(PhenoData);

	# run QC
	r.squared <- positive.control.qc(raw.data = NanoString.DNA.raw);

	# plot results
	make.positive.control.plot(
		correlations = r.squared,
		covs = PhenoData
		);

## End(Not run)

uclahs-cds/public-R-NanoStringNormCNV documentation built on May 31, 2024, 9:09 p.m.