convertRDI - Convert RDI measures

## Description¶

Method to convert RDI values to fold/percent change

## Usage¶

``````convertRDI(d, models = NULL, calcSD = FALSE)
``````

## Arguments¶

d
Distance matrix (as produced by calcRDI), or a vector of distances.
models
Set of RDI models, as produced by rdiModel. If `NULL`, RDI models will be calculated based on the attributes in the distance matrix.
calcSD
logical; if `TRUE`, standard deviations for each estimate will be returned.

## Value¶

A list containing either one or two features:

 *pred* The converted predictions; same length as `d`.

## Details¶

The convertRDI function works by first generating a model for the RDI values at a given repertoire size and feature count using the rdiModel function (see that method’s help file for more details). The RDI models predict the average log-fold/percent change across a range of RDI values, and allows us to convert RDI to a more stable and interpretable metric.

In addition to the average log-fold or percent change value, rdiModel also generates models for the standard deviation at each RDI value. This is useful for understanding the confidence intervals around the fold change estimate.

## Examples¶

``````#create genes
genes = sample(letters, 10000, replace=TRUE)
#create sequence annotations
seqAnnot = data.frame(donor = sample(1:4, 10000, replace=TRUE))
#calculate RDI
d = rdi(genes, seqAnnot)

##convert RDI to actual 'lfc' estimates and compare
dtrue = convertRDI(d)\$pred
plot(d, dtrue)

``````

``````
##look at SD ranges around lfc estimates
dtrue = convertRDI(d, calcSD=TRUE)

##plot using ggplot2
library(ggplot2)
x = as.numeric(d)
y = as.numeric(dtrue\$pred)
sd = as.numeric(dtrue\$sd)
qplot(x,y)+geom_errorbar(aes(x=x, ymin=y-sd, ymax=y+sd))
``````