do_elbow_rnaseq {ELBOW} | R Documentation

## Calculates fold values from an MArrayLM object.

### Description

Performs the ELBOW fold change test on an CountDataSet from DESeq object. This is a wrapper class to help integrate the ELBOW method into Bioconductor. followed tutorial from: http://cgrlucb.wikispaces.com/Spring+2012+DESeq+Tutorial

### Usage

      do_elbow_rnaseq(rnaSeq)

### Arguments

`rnaSeq` | is the CountDataSet object to analyze.

### Value

a matrix specified as follows

- columns — (1) “up_limit”, the upper ELBOW fold-change cut-off value; (2) “low_limit”, the lower ELBOW fold-change cut-off value

- rows — one row per sample, specified by the parameter “columns.”

### Examples

    # install the DESeq libraries
    		#if (!requireNamespace("BiocManager", quietly=TRUE))
        		#install.packages("BiocManager")
    		#BiocManager::install("DESeq")

    		## download the table
    		library("DESeq")

    		# the following bam file dataset was obtained from:
    		# http://cgrlucb.wikispaces.com/file/view/yeast_sample_data.txt
    		# it has been downloaded into this package for speed convenience.
    		filename <- system.file("extdata", "yeast_sample_data.txt", package = "ELBOW")

    		count_table <- read.table(filename, header=TRUE, sep="\t", row.names=1)
    		expt_design <- data.frame(row.names = colnames(count_table), condition = c("WE","WE","M","M","M"))
    		conditions = expt_design$condition
    		data <- newCountDataSet(count_table, conditions)
    		data <- estimateSizeFactors(data)
    		data <- as(data, "CountDataSet")
    		## data <- estimateVarianceFunctions(data)
    		data <- estimateDispersions(data)

    		# this next step is essential, but it takes a long time...
    		# so, just like a good cooking show we will skip this step
    		# and load a finished version.
    		#results <- nbinomTest(data, "M", "WE")

    		# The below two code lines load a copy of the above dataset
    		# which has already been processed by:
    		#     results <- nbinomTest(data, "M", "WE")
    		# For your own real data, you must use:
    		#     results <- nbinomTest(data, "M", "WE")'
    		# Instead of the two lines below:
    		data(yeast_nbinomTest_results, package="ELBOW")
    		results <- yeast_nbinomTest_results

    		# obtain the elbow limit for the dataset
    		# the final step in the analysis pipeline
    		do_elbow_rnaseq(results)

[Package ELBOW version 1.26.0 Index]