classpi: Classification

Description Usage Arguments Value Author(s) Examples

View source: R/nempi_main.r

Description

Builds and uses different classifiers to infer perturbation profiles

Usage

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classpi(
  D,
  unknown = "",
  full = TRUE,
  method = "svm",
  size = NULL,
  MaxNWts = 10000,
  ...
)

Arguments

D

either a binary effects matrix or log odds matrix as for Nested Effects Models (see package 'nem')

unknown

colname of samples without mutation data, E.g. ""

full

if FALSE, does not change the known profiles

method

either one of svm, nn, rf

size

parameter for neural network (see package 'nnet')

MaxNWts

parameters for neural network (see package 'nnet')

...

additional parameters for mnem::nem

Value

plot

Author(s)

Martin Pirkl

Examples

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D <- matrix(rnorm(1000*100), 1000, 100)
colnames(D) <- sample(seq_len(5), 100, replace = TRUE)
Gamma <- matrix(sample(c(0,1), 5*100, replace = TRUE, p = c(0.9, 0.1)), 5,
100)
Gamma <- apply(Gamma, 2, function(x) return(x/sum(x)))
Gamma[is.na(Gamma)] <- 0
rownames(Gamma) <- seq_len(5)
result <- classpi(D)

cbg-ethz/nempi documentation built on May 4, 2021, 9:44 a.m.