RNASeqDifferentialAnalysis_CMD: RNASeqDifferentialAnalysis_CMD

Description Usage Arguments Value Author(s) Examples

View source: R/cmd_batch_rnaseq_differential_analysis.R

Description

This function will run differential analysis on ballgown, DESeq2 and edgeR in R shell.
This function do following things :

  1. ballgown analysis
    Raw reads are normalized into FPKM values
    The main statistic test in ballgown is paramatic F-test comparing nested linear models

  2. DESeq2 analysis
    Median of rations normalization(MRN) is used in DESeq2 for raw reads count normalization.
    Sequencing depth and RNA composition is taken into consideration is this normalization method.
    The main statistic test in DESeq2 is negative binomial distribution.

  3. edgeR analysis
    Raw reads are normalized by TMM and library size. (run calcNormFactors() to get a DGEList, and then run cpm() on that DGEList)
    The main statistic test in edgeR is trimmed mean of M-values(TMM).

If you want to run differential analysis on ballgown, DESeq2, edgeR for the following RNA-Seq workflow in R shell, please see RNASeqDifferentialAnalysis() function.

Usage

1
2
3
4
5
6
7
RNASeqDifferentialAnalysis_CMD(RNASeqRParam, which.trigger = "OUTSIDE",
  INSIDE.path.prefix = NA, Pre_DE.visualization = TRUE,
  Post_DE.visualization = TRUE, ballgown.run = TRUE,
  ballgown.pval = 0.05, ballgown.log2FC = 1, DESeq2.run = TRUE,
  DESeq2.pval = 0.1, DESeq2.log2FC = 1, edgeR.run = TRUE,
  edgeR.pval = 0.05, edgeR.log2FC = 1, run = TRUE,
  check.s4.print = TRUE)

Arguments

RNASeqRParam

S4 object instance of experiment-related parameters

which.trigger

Default value is OUTSIDE. User should not change this value.

INSIDE.path.prefix

Default value is NA. User should not change this value.

Pre_DE.visualization

Default TRUE. Whether to visualize pre-DE analysis results.

Post_DE.visualization

Default TRUE. Whether to visualize post-DE analysis results.

ballgown.run

Default TRUE. Logical value whether to run ballgown differential analysis.

ballgown.pval

Default 0.05. Set the threshold of ballgown p-value to filter out differential expressed gene.

ballgown.log2FC

Default 1. Set the threshold of ballgown log2 fold change to filter out differential expressed gene.

DESeq2.run

Default TRUE. Logical value whether to run DESeq2 differential analysis.

DESeq2.pval

Default 0.05. Set the threshold of DESeq2 p-value to filter out differential expressed gene.

DESeq2.log2FC

Default 1. Set the threshold of DESeq2 log2 fold change to filter out differential expressed gene.

edgeR.run

Default TRUE. Logical value whether to run edgeR differential analysis.

edgeR.pval

Default 0.05. Set the threshold of edgeR p-value to filter out differential expressed gene.

edgeR.log2FC

Default 1. Set the threshold of edgeR log2 fold change to filter out differential expressed gene.

run

Default value is TRUE. If TRUE, 'Rscript/Environment_Set.R' will be created and executed. The output log will be stored in 'Rscript_out/Environment_Set.Rout'. If False, 'Rscript/Environment_Set.R' will be created without executed.

check.s4.print

Default TRUE. If TRUE, the result of checking RNASeqRParam will be reported in 'Rscript_out/Environment_Set.Rout'. If FALSE, the result of checking RNASeqRParam will not be in 'Rscript_out/Environment_Set.Rout'.

Value

None

Author(s)

Kuan-Hao Chao

Examples

1
2
3
4

HowardChao/RNASeqR documentation built on Sept. 6, 2019, 8:52 a.m.