PLSR_from_file_and_predict_second_dataset: Partial Least Squares and predict second dataset

In graeberlab/small.cell.project: small.cell.project

Description

Builds PLS model from training dataset and predicts second dataset Writes out predicted.scores of the second dataset Plots original PLS, projected samples only, and projected samples ontop of original PLS

Usage

PLSR_from_file_and_predict_second_dataset(file, file2, sample.names,
  sample.type, y.response, train_string, test_string, title = "PLSR",
  comp.x = "comp.1", comp.y = "comp.2", comps = 2, labels = F,
  saveplot = T, savetype = ".png", w = 8, h = 6,
  legendname = "default", scale = F, plot_both = T,
  colpalette = NULL, shape.palette = NULL, ellipses = T,
  conf = 0.9, varimax = F, varimax.comp = 2, output_folder = "./",
  TCGA = F, threshold = 3, do.legend = T)

Arguments

file	file for X matirx
file2	file for test data matrix
sample.names	Vector of sample names in X matrix
sample.type	vector of sample groups
y.response	numeric vector of response values in same order as samples
train_string	string of training data to insert in file name of predicted scores
test_string	string of data being tested to insert in file name of predicted scores
title	title of the plot
comp.x, comp.y	comps to display
labels	label the plot, default = T
saveplot	whether to save the plot, default is F
savetype	the type of plot to save,options are ".pdf" or ".png"
w	is width of plot to be saved
h	is height of plot to be saved
legendname	is the legend name
scale	default=T
plot_both	if true plots both training and test set in color
colpalette	allows you to put in a color palette of form c("#F87660", "#39B600",....etc) to manually assign colors
shape.palette	allows you to put in a shape palette of form c(1, 3,....etc) to manually assign shapes
varimax	If T performs Varimax rotation,
varimax.comp	# of varimax components, kind of hacky, keep this # the same as # of comps. Will fix later.
output_folder	the folder to output to, default is ./ i.e. current folder
TCGA	predicted files are from TCGA, barcodes separated by periods, so remove normal samples, default is FALSE
comp	number of components to compute
sample.names2	Vector of sample names in 2nd dataset, if needed
sample.type2	Vector of sample types in 2nd dataset, if needed

graeberlab/small.cell.project documentation built on May 12, 2019, 5:16 p.m.