ERGO 2.0 presents differential gene expression analysis within a genome's metabolic context.  Quickly discover which subsystems are over and under expressed. Choose contrasts, draw graphs and export with ease.

 

Pinpoint and select significantly over or under expressed genes using ERGO 2.0's interactive Volcano Plot.  Painlessly export graphs of expression profiles for presentation and publication.

 
 
 

Data clustering allows the identification of expression patterns. Choose from a variety of correlation methods for clustering and deepen your understanding by narrowing your selection and viewing subplots.

 
 

Verify consistency among biological and technical replicates by examining visualizations generated from your data.  ERGO 2.0 allows simple removal of inconsistent values from analysis and easy re-computation of clustering, PCA, or differential gene expression.

Features that ERGO 2.0 provides for RNA-Seq and expression analytics

  • Quality analytics of sequence reads

  • RNA-Seq alignment using academically proven software (Bowtie 2, TopHat, and more)

  • RNA-Seq read summarization (featureCounts, Cufflinks, HTSeq, Sailfish)

  • RNA-Seq sample quality analytics

  • Data normalization using R with published techniques (limma, voom, DESeq2)

  • Customized hierarchical cluster diagram

  • Customized differential gene expression analysis integrated with our huge pathway database and Gene Ontology (GO).

  • Customized Principal Components Analysis (PCA) plots

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