positiveQC: Calculate positive control statistics

In calebclass/NanoTube: An Easy Pipeline for NanoString nCounter Data Analysis

Calculate positive control statistics

Description

Calculate the linearity and scale factors of positive control genes, and plot the expected vs. observed counts for each sample.

Usage

positiveQC(ns, samples = NULL, expected = NULL)

Arguments

ns	NanoString data, processed by 'processNanostringData' with normalization set to 'none' or with output.format set to 'list'.
samples	A subset of samples to analyze (either a vector of sample names, or column indexes). If NULL (default), will include all samples.
expected	The expected values of each positive control gene, as a numeric vector. These are frequently provided by NanoString in the 'Name' field of the genes, in which case those values will be read automatically and this option can be left as NULL (the default).

Value

A list object containing:

tab	The table of positive control statistics, included the positive scale factor and the R-squared value for the expected vs. measured counts
plt	An object containing the positive control plots. This gets cumbersome if there are lots of samples.

Examples

example_data <- system.file("extdata", "GSE117751_RAW", package = "NanoTube")
sample_data <- system.file("extdata", 
                           "GSE117751_sample_data.csv", 
                           package = "NanoTube")

# Process data first. Must be output as a "list" or without normalization to
# obtain positive control statistics
dat <- processNanostringData(example_data, 
                             sampleTab = sample_data, 
                             groupCol = "Sample_Diagnosis",
                             normalization = "nSolver", 
                             bgType = "t.test", 
                             bgPVal = 0.01,
                             output.format = "list")

# Generate positive QC metrics for all samples
posQC <- positiveQC(dat) 

# View positive QC table & plot
head(posQC$tab)
posQC$plt

# Plot for only the first three samples
posQC <- positiveQC(dat, samples = 1:3)
posQC$plt

calebclass/NanoTube documentation built on Nov. 21, 2023, 12:31 p.m.