The NOISeq tutorial can be downloaded from Bioconductor website. Click here.

In NOISeq package, you can find not only the method to compute differential expression between two experimental conditions from RNA-seq data, but also other functions in order to learn more about saturation, contamination or other biases in your data as well as to explore the differential expression results.

Please, follow these instructions to run NOISeqBIO:

1) Install NOISeq Bioconductor package (see Downloads) and load it: library(NOISeq).

2) Download the zip file containing the R scripts for NOISeqBIO (from Downloads) and unzip it.

3) To load the NOISeqBIO functions in R from your working directory:

# Remember you have to change this path if you are not in the same directory:
> mypath = "NOISeqBIO_v00"  

> source(file.path(mypath, "auxiliar.R"))
> source(file.path(mypath, "MDbio.R"))
> source(file.path(mypath, "allMDbio.R")) 
> source(file.path(mypath, "noiseqbio.R"))
> source(file.path(mypath, "classes.R"))
> source(file.path(mypath, "normalization.R"))
> source(file.path(mypath, "fewreplicates.R"))

4) Read your data as in NOISeq (see the following example with Marioni's data) to convert them to a NOISeq object:

> data(Marioni)
> mydata = readData(data = mycounts, factors = myfactors)

Follow this example of application of NOISeqBIO with your own data:

> mydata = readData()  # as in NOISeq (please go to the Tutorial for more information)
> myresults = noiseqbio()
> myq = 0.95 # Cutoff for the probability of differential expression (1-FDR)
> mydeg = 

Please, note that you can choose the same normalization procedures as in NOISeq.