DEGseq: An R package to identify differentially expressed genes from RNA-Seq data.

Description

Identify Differentially Expressed Genes from RNA-seq data.

Parameters

1. Dataset: 2 sample groups.
2. Method: The inference algorithm:
   1. LRT: Likelihood Ratio Test (Marioni et al. 2008).
   2. FET: Fisher's Exact Test (Joshua et al. 2009).
   3. MARS: MA-plot-based method with Random Sampling model (Wang et al. 2009).
   4. MATR: MA-plot-based method with Technical Replicates (Wang et al. 2009).
3. P-value/FdrSignificance Cutt-off method and value.
4. Output: DESeq creates a standard MeV viewer nodeo nthe left tree which conists of heatmaps and tables of both significant, non-significant and a combined list of genes.

How to Run DEGseq

1. Load RNAseq type data
2. Launch DEGseq from ToolBar -> Statistics -> DEGseq
3. Assign samples to 2 groups or leave them out
4. Choose inferecne method
5. Choose significance coutt-off method (p-value or fdr) and specify a value
6. Hit OK