Analysis.DISEXP: Perform correlation analysis based on RNA distance and Gene...

Description Usage Arguments Value Author(s) Examples

View source: R/Analysis.R

Description

Analysis.DISEXP is a complete analysis based on user selection of linear or log regression. The gene expression is calculated as the absolute differences between sampled and normal gene expression data. Analysis also export sets of graphs to facilitate in model selection and analysis result validation.

Usage

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Analysis.DISEXP(
  dis.name,
  dis.distance,
  exp.tumor,
  exp.sample,
  method = "linear",
  showPlot = FALSE
)

Arguments

dis.name

Set of name of RNA distance

dis.distance

Set of RNA distance between mutate and original data

exp.tumor

Set of reads from gene expression from tumor samples

exp.sample

Set of reads from gene expression from normal samples (usually blood sample)

method

Selection of linear or gaussian log link function for regression (linear or log)

showPlot

TRUE and FALSE variable if TRUE the output image will be shown on the run

Value

Returns an S3 object of class DISEXP with results. list of output stats from the model

Author(s)

Sijie Xu, sijie.xu@mail.utoronto.ca

Examples

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disexp <- Analysis.DISEXP(
             dis.name = c("hsa-let-7a-1", "hsa-let-7a-1",
             "hsa-let-7a-3", "hsa-let-7a-3", "hsa-let-7a-3"),
             dis.distance = as.integer(c(10, 35, 91, 100, 92)),
             exp.tumor = c(98691, 49201, 57540, 148702, 97721),
             exp.sample = c(23495, 23310, 13274, 19337, 14389))

JackXu2333/rseAnalysis documentation built on Dec. 31, 2020, 1:10 p.m.