MINT.PLSR_from_file_and_predict_second_dataset: MINT Partial Least Squares and predict second dataset

Description Usage Arguments

Description

Builds MINT 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

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MINT.PLSR_from_file_and_predict_second_dataset(..., file2, sample.names,
  sample.type, y.response, sample.names2 = NULL, sample.type2 = NULL,
  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,
  study.train.names, study.test.names, threshold = 3)

Arguments

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

sample.names2

Vector of sample names in 2nd dataset, if needed

sample.type2

Vector of sample types in 2nd dataset, if needed

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

study.train.names

vector sample types that are in group 1 in the training studies e.g. c("NEPC","CRPC") (max 2)

study.test.names

a string of the sample type that is in the test group , e.g. "PAAD"

threshold

threshold for predictions

file

file for X matirx

comp

number of components to compute


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