spaceMaker: Creates PhysioSpaces

In JRC-COMBINE/PhysioSpaceMethods: Creates and uses physio spaces as a dimension reduction mapping

Description

This function uses 'Big Data' to make robust 'Physiological Vectors' in N dimensional spaces, within which you can map new data to extract physiological information from a new data set.

Usage

spaceMaker(
  GeneExMatrix,
  DESIGN = NA,
  CONTRASTs = NA,
  Output = "PhysioScore",
  LinearOrRNASeq = "Linear",
  NumbrOfCores = 1
)

Arguments

GeneExMatrix	A matrix of input gene expressions or a SummarizedExperiment object, based on which the Physiological Space is made. In case of a matrix, GeneExMatrix is supposed to have genes as rows and samples as columns. Corresponding Entrez Gene IDs must be assigned to 'rownames', and name of each sample should be written in 'colnames' of the matrix. In case of a SummarizedExperiment object, GeneExMatrix must have a component named 'EntrezID' in its rowData. It is also expected (but not mandatory) for GeneExMatrix to have a component named 'SampleName' in its colData. The gene expressions in GeneExMatrix is extracted by the function assay(), meaning in case GeneExMatrix contains multiple assays, only the first one is used. Unless 'DESIGN' and 'CONTRASTs' inputs are provided by the user, spaceMaker supposes the label of the first column (colnames(GeneExMatrix)[1]) to be the reference of the experiment and uses all the samples with this label as control.
DESIGN	(Optional) Design matrix of GeneExMatrix, made by the function model.matrix(). If it's not provided, spaceMaker() will make a design matrix based on sample names of GeneExMatrix.
CONTRASTs	(Optional) character vector or list specifying contrasts. If it's not provided, spaceMaker() will make the CONTRASTs with the assumption that sample names of first column is the label of the control or reference. REMEMBER that expected user-defined CONTRASTs format changes based on the LinearOrRNASeq input: in case LinearOrRNASeq='Linear', CONTRASTs is expected to work as an input for limma::makeContrasts(). And when LinearOrRNASeq='RNASeq', CONTRASTs is used as an input for DESeq2::results().
Output	A character specifying the output format of spaceMaker(). The default value is 'PhysioScore', which will return -log2(p value)*sign(fold change). It is also possible to obtain fold change by Output='FoldChange', or obtain the fitted model by having Output ='Model'.
LinearOrRNASeq	A character which determines what type of modelling is ought to be used when making the PhysioSpace. If it's possible to do linear modelling on the data, e.g. data is log normal micro-array gene expression data or limma::voom-transformed RNA-seq data, then LinearOrRNASeq should be 'Linear'. In this case limma package is used in the calculations. But in case your GeneExMatrix input is an RNA-seq count matrix, you should pass 'RNASeq' to LinearOrRNASeq. In this case DESeq2 package is used for calculations.
NumbrOfCores	Number of cpu-cores to be used (only in RNASeq mode). Default is 1 which will result in the program running in serial. If you assign a number higher than 1, BiocParallel::MulticoreParam is called to make a parallel back-end to use. Assigning a number higher than parallel::detectCores() will result in an error. You can also pass a BiocParallelParam instance to be used as parallel back-end. Remember that on Windows, the default MulticoreParam back-end doesn't work so you have to use another back-end, e.g. Snow by calling BiocParallel::SnowParam(). For more information, check the documentation of BiocParallel package.

Value

Depending on the 'Output' argument, the returned value is either a matrix, or a model. If Output = "PhysioScore", a matrix is returned, with genes in rows and Physiological axes on the columns. In this case, values inside this matrix are PhysioScores (-log2(p value)*sign(fold change)). In case of Output = "FoldChange", a matrix of fold changes is returned. And if Output = "Model", the fitted model by limma::lmFit() or DESeq2::DESeq() is returned. REMEMBER that when user provides 'DESIGN' input argument, colnames of the returned matrix remains empty and are needed to be assigned by the user.

Examples

 INPTMat <-
   matrix(
     data = rnorm(n = 18000, mean = 8, sd = 6),
     nrow = 2000,
     dimnames = list(paste0("g", 1:2000), c(
       rep("Ctrl", 3), rep("Cancer1", 3), rep("Cancer2", 3)
     ))
   ) #Simulated DNA-array gene expression matrix
 LinearSpaceOfINPTMat <- spaceMaker(GeneExMatrix = INPTMat)

 INPTMatRNASeq <-
   matrix(
     data = rnbinom(n = 18000, size = 1.5, prob = 0.01),
     nrow = 2000,
     dimnames = list(paste0("g", 1:2000), c(
       rep("Ctrl", 3), rep("Cancer1", 3), rep("Cancer2", 3)
     ))
   ) #Simulated RNA-seq gene expression matrix
 NotLinearSpaceOfINPTMatRNASeq <-
   spaceMaker(GeneExMatrix = INPTMatRNASeq, LinearOrRNASeq = "RNASeq")


 library(SummarizedExperiment)
 INPTMat_SE <- SummarizedExperiment(
     assays = list(GEX = INPTMat),
     rowData = data.frame("EntrezID" = rownames(INPTMat)),
     colData = data.frame("SampleName" = colnames(INPTMat))
 ) #Simulated DNA-array gene expression SummarizedExperiment obj.
 LinearSpaceOfINPTMat_SE <- spaceMaker(GeneExMatrix = INPTMat_SE)

JRC-COMBINE/PhysioSpaceMethods documentation built on July 27, 2021, 12:53 p.m.