runDESeq

A matrix that includes all the expression raw counts,
rownames has to be the gene, isoform or region names/IDs

data, 

is a vector that includes the columns that are going
to be analyzed. These columns has to match with the given data.

columns, 

experimental conditions. The order has to match
with the column order

conds, 

DESeq2 fitType, it can be 'parametric', 
'local', 'mean'.

fitType, 

to remove unexpressed 
regions/genes/isoforms this cutoff is used

non_expressed_cutoff, 


Run DESeq2 algorithm on the selected conditions.  Output is
to be used for the interactive display.


Bioinformatics platform containing interactive plots and tables
for differential gene and region expression studies. Allows visualizing
expression data much more deeply in an interactive and faster way. By
changing the parameters, user can easily discover different parts of the
data that like never have been done before. Manually creating and looking
these plots takes time. With this system users can prepare plots without
writing any code. Differential expression, PCA and clustering analysis are
made on site and the results are shown in various plots such as scatter,
bar, box, volcano, ma plots and Heatmaps.

runDESeq: runDESeq

Description

Usage

Arguments

Value

Examples