visualizePrediction: This is a Shiny web application for the visualization of...

Description Usage Arguments

View source: R/response_viewer.R

Description

This is a Shiny web application for the visualization of hidden states of LSTM models from the package deepG. It also comes with the possibility to use own trained models.

Usage

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visualizePrediction(
  sample = "",
  states = FALSE,
  model.path = "",
  fasta.path = "",
  states.path = "",
  start_position = 0,
  end_position = 800,
  batch.size = 200,
  vocabulary = c("l", "a", "g", "c", "t"),
  layer_depth = 1,
  cell_number = 1,
  step = 1,
  padding = TRUE
)

Arguments

sample

character input string of text

states

if states = TRUE, then load states from states_path

model.path

path to trained model

fasta.path

path to fasta files

states.path

path to the .h5 file with the calculated states

start_position

start from the dygraph

end_position

end from the dygraph

batch.size

number of samples to evaluate at once

vocabulary

used vocabulary

layer_depth

depth of layer to evaluate

cell_number

cell_number showed in the dygraph

step

frequency of sampling steps

padding

TRUE/FALSE generate states for the first maxlen nucleotides


hiddengenome/altum documentation built on April 22, 2020, 9:33 p.m.