precision: Assess the precision of the expression estimates

In mccallm/miRcomp-shiny: Tools to assess and compare miRNA expression estimatation methods

Description

This function assesses the within-replicate precision for each feature.

Usage

precision(object1, qcThreshold1, object2=NULL, qcThreshold2=NULL,
          commonFeatures=TRUE, statistic=c("sd","cv"),
          scale=c("none","log","log10"), bins=3,
          label1=NULL, label2=NULL) 

Arguments

object1	a list containing two elements: ct (the expression estiamtes) and qc (quality scores)
qcThreshold1	a numeric threshold corresponding to object1$qc below which values are considered low quality.
object2	an optional second list of the same format as object1, used to compare two methods.
qcThreshold2	a numeric threshold corresponding to object2$qc below which values are considered low quality.
commonFeatures	if TRUE and object2 is non-NULL, only high quality non-NA features in common between both objects are used.
statistic	whether to compute the standard deviation (sd) or coefficient of variation (cv).
scale	optional scaling of the values. This can help with visualizing the distributions.
bins	the number of bins to divide the data into.
label1	optional label corresponding to object 1 to be used in plotting.
label2	optional label corresponding to object 2 to be used in plotting.

Value

A boxplot of either the standard deviation or coefficient of variation stratified by expression is produced. The values plotted in each box of the boxplot are returned.

Author(s)

Matthew N. McCall

Examples

  data(lifetech)
  tmp1 <- precision(object1=lifetech,qcThreshold1=1.25)
  data(qpcRdefault)
  tmp2 <- precision(object1=lifetech,qcThreshold1=1.25,
           object2=qpcRdefault,qcThreshold2=0.99)

mccallm/miRcomp-shiny documentation built on May 29, 2019, 4:41 a.m.