pred: Predict the exposure status of an independent sample.

In BioHPC/iCAT: immune Cell Analysis Tool

Description

Predict the exposure status of an independent sample.

Usage

pred(comb, indpt, names, field, count, copyrange)

Arguments

comb	List containing both negtive (n) and positive (v) clonotype percentages.
indpt	Vector of independent samples file paths.
names	Vector of labels for independent samples.
field	String containing the column or columns (space-delimited) of interest.
count	String containing the column name for colontype counts.
copyrange	Integer Vector of the min and max copy of a sequence, within a sample, to be considered.

Value

Matrix with % correct predictions from training data.

Examples

FIELD <- "vGeneName aminoAcid jGeneName"
COUNT <- "copy"
P_CUTOFF <- 0.1
MIN_PUBLIC <- 2
COPY_RANGE <- "1 99"


listPos <- tsvDir(system.file("extdata", "Post", package="iCAT"))
listNeg <- tsvDir(system.file("extdata", "Pre", package="iCAT"))

naive <- readTrn(listNeg, FIELD, COUNT, COPY_RANGE, "naive")
vaccs <- readTrn(listPos, FIELD, COUNT, COPY_RANGE, "vacc")  

mod <- train(naive, vaccs, listNeg, listPos, FIELD, COUNT, COPY_RANGE, P_CUTOFF, MIN_PUBLIC, NULL)
pred(mod, system.file("extdata", "Pre", "KJW100_HLA-A2_10_PRE.tsv", package="iCAT"), "unknown-sample-label", FIELD, COUNT, COPY_RANGE)

BioHPC/iCAT documentation built on Oct. 30, 2021, 3:12 p.m.